>WORKSHEET – ANOVA ASSIGNMENT
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Please select a choice 0 Please select a choice 0 Please select a choice 0 Please select a choice 0 Please select a choice Please select a choice 0 0 Please select a choice Please select a choice 0 0 Please select a choice 0 ‘ for each assumption that needs to be satisfied when conducting a One-Way Anova
IMPORTANT: For each assumption, only answer this if you selected “Yes” in the cell to the left. If you selected “ ,” the answer choice will go black in this column
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Please select a choice 0 Please select a choice 0 0 0 Please select a choice 0 Mean difference = 0 Mean difference = 0 Please select a choice 0 Please select a choice 0 SPECIAL REQUIRED WORKSHEET FOR ASSIGNMENT ON ANOVA First things first… You are required to show your SPSS output when you submit your assignment. Please indicate whether you intend to do so. Section 1 – DATA CONTEXT: In this section, you’ll be making choices from drop-down menus. Section 2 – TESTING ASSUMPTIONS: In this section, you’ll be using drop-down menus to choose ‘yes’ or ‘no’ Section 3 – Research Question, Hypotheses, Alpha Level: In this section, you’ll be using drop-down menus Section – Interpretation: In this section, you’ll be using drop-down menus and filling in the blanks Section – Conclusion: In this section, you’ll be using drop-down menus
Sections is supposed to be what? It’s a variable that represents the different sections of a class, right? As such, even if those sections are numbered, this is a variable where those numbers are just labels — they’re just arbitrary words. If that’s true, then this is what kind of a variable? Quiz3 is a variable representing meaningful NUMBERS. So, what kind of variable could this one be? Want to hear something weird? Turns out that even if the DV were not normally distributed, we could still do a one-way ANOVA. Hmmm…. Could this be a hint about the second assumption below? All the numbers here (Shapiro-Wilk and Levene) come right off SPSS output. Think about what variables we’re focused on. That alone should help you frame this up. Remember that this is not the same thing as the p-value but we will end up comparing them at some point. All of this stuff comes right out of the SPSS output. Right out! No calculations.
Hint: Down below, I’m asking for the results of this test. So, uh, should the test be performed? Um, well…
To calculate effect size (eta squared), use the formula to the right. You’ll find Sum of Squares (SS) for between-groups and total, on your SPSS output. You could easily google the strengths and limitations of a one-way ANOVA. You’ll also find them in your materials. Either way, you’re all set. This all comes out of your post hoc test SPSS output. In your DAA, please explain what all this is. It’s not enough just to list a bunch of numbers. SCORING x First off, you did a great job of working through the DAA. You’ve produced a compelling narrative that stands on its own, about an exercise in one-way ANOVA. This DAA demonstrates real engagement with the concepts. When I read your DAA, I can SEE the learning you did. This is well done, indeed. %
Please select a choice Yes 1 0% No Please select a choice 2 0% 0% 20% 5% Please select a choice 20% 0% 10% 0% 10% 10% Please select a choice Are there significant differences between Quiz 3 grades among the 3 sections? Are there significant differences between Quiz 3 grades among men and women? What is the relationship between socioeconomic status and Quiz 3 grades? First off, you did a great job of working through the DAA. You’ve produced a compelling narrative that stands on its own, about an exercise in one-way ANOVA. This DAA demonstrates real engagement with the concepts. When I read your DAA, I can SEE the learning you did. This is well done, indeed. More than one thing went wrong here if I’m reading your worksheet and full-length paper correctly. Just so you know, Sections 3 should be a nominal predictor variable, while Quiz3 should be a ratio outcome variable, with the sample size equal to . I’d check to see specifically where things got a little derailed in this part of the assignment, and then consult the course materials as needed to nail this down. You’ll need these skills as you continue along in your academic journey, so it’s worth buttoning them up now. effect size (eta2).
determination of whether the comparison was significant; Mean difference, p-level, determination of whether the comparison was significant; Mean difference, determination of whether the comparison was significant;
. Does age correlate with Quiz 3 grades for the 3 sections? There is no difference between Quiz 3 grades in the 3 sections. There is no difference between grades received on quiz3 based on one’s gender. SES has no impact on grades received for quiz3. Hi, 105 Please select a choice When you submit your work, will you include the SPSS output for the results of the ANOVA test? Section 2 of the Rubric: This one asked you all the standard stuff about the variables you’re using in this analysis. Why is this important? We’ve got to know what we’re examining when we do a research study, and how we would go about measuring those things. Section 2 of the Rubric: This one asked you all the standard stuff about the variables you’re using in this analysis. Why is this important? We’ve got to know what we’re examining when we do a research study, and how we would go about measuring those things. More than one thing went wrong here if I’m reading your worksheet and full-length paper correctly. Just so you know, Sections 3 should be a nominal predictor variable, while Quiz3 should be a ratio outcome variable, with the sample size equal to 105. I’d check to see specifically where things got a little derailed in this part of the assignment, and then consult the course materials as needed to nail this down. You’ll need these skills as you continue along in your academic journey, so it’s worth buttoning them up now. Section 3 of the Rubric: You may be thinking, “Why do I have to wrestle with these assumptions again? I already went through this with the t-test assignment.” Well, if you recognized that the assumptions of an ANOVA are the same as those for a t-test, then you are right! You did go through this already. But it’s important that we consider these with respect to ANOVAs. I noticed more than 2 problems in the assumptions part of the assignment. Here’s how that section should have looked: When asked to indicate which assumptions need to be satisfied to conduct an ANOVA, the correct answers were independence of observations, outcome (or dependent) variable is quantitative and normally distributed, and homogeneity of variables. Everything else didn’t have to be satisfied. When asked to evaluate whether or not these assumptions had been satisfied in the data set with which you were working, the answer is yes for everything except the one saying that the DV has to be quantitative and normally distributed. Section 4 of the Rubric: This is an area where we’ve all had a good chance to practice during the course. Hypothesis testing is core to what we do as researchers. Even if we don’t intend to do any research beyond our experience at Capella, this sort of training will make us better critical thinkers, which is certainly useful across professions. I could see from your assignment submissions that you made at least one error here. I’d revisit the course materials and get some more practice with the conceptual framework underlying hypothesis testing. Section 5: The previous sections were mostly aimed at seeing whether you understood the basic principles of ANOVAs. This section is focused on evaluating how well you can actually do one. As it turns out, you may need to do some work in this area because I detected a bunch of errors in your reporting of means and standard deviations. It could be that something went wrong when you attempted to generate the output or it could be something conceptual. Either way, it’s worth taking a few steps back and retracing your steps. . Let’s turn now to the interpretive piece. Based on your ANOVA results, the null hypothesis should indeed be rejected and the post-hoc test should be performed. At least one of your answers differed from this so I think it’s worth diving back into the ANOVA material and getting a sense of how to interpret your ANOVA findings. Finally, in the section asking you to report the results of your Tukey HSD test, over a third of the items were incorrect. The specific items include the following: Section 1 vs. Section 2 – Mean difference, p-level, determination of whether the comparison was significant; Section 1 vs. Section 3 – Mean difference, p-level, determination of whether the comparison was significant; Section 2 vs. Section 3 – Mean difference, determination of whether the comparison was significant; Let’s turn now to the interpretive piece. Based on your ANOVA results, the null hypothesis should indeed be rejected and the post-hoc test should be performed. At least one of your answers differed from this so I think it’s worth diving back into the ANOVA material and getting a sense of how to interpret your ANOVA findings. Section 6: Here you had to address strengths and limitations. You scored at least one wrong here so I would check out how this happened and make sure you’ve got a lock on it. Section 6: Here you had to address strengths and limitations. You scored at least one wrong here so I would check out how this happened and make sure you’ve got a lock on it. Section 6: Here you had to address strengths and limitations. You scored at least one wrong here so I would check out how this happened and make sure you’ve got a lock on it. The previous GPA correlates with the number of correct final exam scores. Gender correlates with the previous GPA. Please select a choice 0.50 0.00 Please select a choice Select ‘Yes’ for each assumption that was satisfied in the data set you’re working with Gender/GPA To evaluate these assumptions, please fill in the blanks with the results of the following tests: 0 0 0 1 0 3 0 0 0 0 3 5 5 Within-Groups Degrees of Freedom, 0 F-value, 0.000 1 0 5 0.000 0 effect size (eta2), 5 Please select a choice 0 5 The last section where you had to evaluate the strength and limitation of a t-test is another of those you-either-know-it,-or-you-don’t kinds of situations. Both of your answers were incorrect, so I’m not sure what happened here. You might just want to check out the course material and get this moving in the right direction again. 5 If you decide to conduct the Tukey HSD post-hoc test, please report your results here (fill in the blanks and use a drop-down menu): 5 Mean difference, p-level, Please select a choice 0 Yes determination of whether the comparison was significant, Mean difference, p-level, 6 Mean difference, Please select a choice It can evaluate whether the sample size needs to be larger. 75 gets a PROFICIENT Running head: JOURNAL ARTICLE SUMMARY 1 JOURNAL ARTICLE SUMMARY 4 Journal Article Summary The journal article selected investigates the effect in which lyrical music has on reading comprehension by adolescents “a variety of child, parent, and familial variables that may predict treatment response” (Anderson & Fuller, 2010). A search was conducted and its purpose was to explore if there were any impacts and what impact if there were any that would come from listening to lyrical music that was popular at the same time as performing a cognitively task that was complex would have on students and their materials for studying along with the basic. The researchers examined data collected from around 334 students that ranged from the 7th and 8th grade. The gender was equal where there were around 172 boys and 162 girls. The studies had to contain “a quantifiable measure of the association between the predictor variable(s) and outcome; d) studies employed a valid and/or reliable predictor and outcome measure; e) studies were published in a peer-reviewed journal and written in the English language” (Anderson & Fuller, 2010). The journal article is relevant to the specialization of Behavior Analysis because it studied the effect of cognitive and comprehensive task and children.
Section 2: Testing Assumptions
The article noted that some of the categories were not homogeneous. The X and Y were linear, which was proved by visual inspection of the tables. Most assumptions were proven. The purpose of this article was to “examine the content effect that lyrical music along with the selection of the moderate playback level of 75 decibel and see its effects while performing the cognitive test. The null hypothesis is that there was a difference that had existed between the reading comprehension scores in the environments with and without music being accepted. The standardized effect sizes displayed in the article where; .0–.1 insubstantial, .1–.3 small, .3–.5 moderate, and .5–1.0 large” (Anderson & Fuller, 2010). These effect sizes where based on correlation coefficients. However, when the researchers combined the data from all of the studies, variable and treatment outcome only resulted in insignificant standardized effect sizes. The article demonstrated that “when lyrical music was used the effects were at a different level for the girls and boys. The girls were at a greater decline in scores under the music environment in comparison to nonmusical. They were at (M= – 5.01) and the boys were at (M= – 3.20). the difference was very significant at F (1, 332) =9.72, p = .002. the total comprehensive score from the students were related to the reading comprehensive from nonmusical environment at r (332) = -.12, p= .03. There was no correlation with the reading comprehensive difference score (music vs. no music) r (332).05, p. = 34, or with the reading comprehension score in the music environment, r (332) = – .09, = p.10. In regard to the null hypothesis, was partially accepted. This is because the study was able to show that females had a slightly higher preference for listening to music when studying than the males did. The journal article used results from studies taken and showed that the association amngst music and intellectual performance is a clear topic which does merit some more investigations especially for adolescents. It looked at the content effect that lyrical music along with the selection of the moderate playback level of 75 decibel and how it affected both male and females while conducting test. We can safely say that there are a lot more studies needed in order to study the interrelationship between different variables and response to lyrical music while reading. Effect of Music on Reading Comprehension of Junior High School Students. Stacey A. Anderson and Gerald B. Fuller from Walden University, 2010. >SPECIAL WORKSHEET u 8a 0 1 0 Please select a choice 1 0 Please select a choice 0 Please select a choice 0 Please select a choice Please select a choice 0 0 Please select a choice Please select a choice 0 0 Please select a choice 0 ‘ for each assumption that needs to be satisfied when conducting a t-test
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uestion relevant to the statistical test
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% confidence interval for the difference between means for males and females
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SPECIAL REQUIRED WORKSHEET FOR U08A1 – t-Tests First things first… You are required to show your SPSS output when you submit your assignment. Please indicate whether you intend to do so. Section 1 – DATA CONTEXT: In this section, you’ll be making choices from drop-down menus. Section 2 – TESTING ASSUMPTIONS: In this section, you’ll be using drop-down menus to choose ‘yes’ or ‘no’ Section – Research Question, Hypotheses, Alpha Level: In this section, you’ll be using drop-down menus Section 4 – Interpretation: In this section, you’ll be using drop-down menus and filling in the blanks Section 5 – Conclusion: In this section, you’ll be using drop-down menus
TWO MAJOR HINTS — (1) Use the EQUAL VARIANCES ASSUMED figures; MAJOR HINTS FOR THE ASSUMPTIONS PORTION — (1) Even if the DV is NOT normally distributed, we can still perform a t-test. (2) Linearity was really important for correlation. Is this assignment about correlation? (3) If homogeneity of variance is not violated, we use the output where equal variance is assumed. MAJOR HINT FOR THE DATA CONTEXT PORTION — Gender is neither interval nor ratio. GPA is not ordinal. Do you see why? MAJOR HINT FOR THIS PORTION — Hypothesis testing is a researcher’s bread and butter. If you’re still having trouble with it, please see the handout on 4d1 from a few weeks ago. MAJOR HINT — To determine whether to reject the null, we look at the p-value. If p<.05, we REJECT the null. SCORING on DAA – lots of explanation and elaboration
Please select a choice x Your DAA flowed from start to finish with learning. Could it have benefited from a bit more explanation in places? Yes (e.g., in the section on assumptions and the interpretation). But overall, I could see the effort. Thank you for making that effort. Yes 1 0% No Please select a choice 2 0% 0% 20% 2% 0% 10% 0% 10% 10% Please select a choice Your DAA flowed from start to finish with learning. Could it have benefited from a bit more explanation in places? Yes (e.g., in the section on assumptions and the interpretation). But overall, I could see the effort. Thank you for making that effort. I noticed in this section was that your measurement of sample size for the data set appears to be incorrect. It should be , reflecting the total number of participants in the study. Importantly, contrary to what you wrote in your assignment, the null hypothesis should be rejected in this case because it is less than , our present alpha level). Why is this the case? Please take a look at the textbook as well as other course and non-course materials to get a better understanding of hypothesis testing. standard deviation for males.
erence, the correct answer should have been 0.28 (rounded), which should have been a relatively manageable sort of calculation.
105 Please select a choice There is a difference in GPA between male and female students. One final thing: When I look over your DAA, I see someone who worked extraordinarily hard to think through and develop this assignment. I do not under any circumstances want you to think that just because I marked some things wrong, took off some points here and there, and wrote a lot of feedback, that you didn’t do well. I think you did REALLY well. This paper is what it looks like to work hard, and even though you may not have gotten everything as correct as you wanted to, I really truly believe with all my heart, that you scored a real victory here. Regardless of what you think about your abilities, you’re in the fight. One final thing: When I look over your DAA, I see someone who worked extraordinarily hard to think through and develop this assignment. I do not under any circumstances want you to think that just because I marked some things wrong, took off some points here and there, and wrote a lot of feedback, that you didn’t do well. I think you did REALLY well. This paper is what it looks like to work hard, and even though you may not have gotten everything as correct as you wanted to, I really truly believe with all my heart, that you scored a real victory here. Regardless of what you think about your abilities, you’re in the fight. There is no difference in GPA between male and female students. Please select a choice Please select a choice It cannot evaluate the means between more than 2 groups. It can evaluate whether there’s a statistically significant difference between 2 groups. The only other thing I noticed in this section was that your measurement of sample size for the data set appears to be incorrect. It should be 105, reflecting the total number of participants in the study. It can predict the required sample size for a follow-up study. Select ‘Yes’ for each assumption that was satisfied in the data set you’re working with Gender correlates with the previous GPA. It looks as if you may not have represented your knowledge correctly (or just didn’t completely nail down that particular piece of knowledge) because I see at least one error in the part where you had to identify assumptions that would need to be satisfied. It could also be that you didn’t completely understand these assumptions, or how to apply them because when I look at your DAA and worksheet, I see at least one case where you misidentified whether an assumption was satisfied in the data set with which you were working. Just so you know what all of the correct answers were, let me list them out. The assumptions that have to be met when conducting a t-test are: Independence of observations; Outcome (or dependent) variable is quantitative and normally distributed; and Homogeneity of variance. Of these, only the first and third were met in this data set. So, all in all, I think you may want to dig back into the materials a bit. Okay, so let’s tackle section 3 of the rubric, the one asking you to evaluate the assumptions that need to be satisfied before doing a t-test. This is the sort of stuff that you either know (based on your reading of the course material) or you don’t. Of course, the real challenge is that once you know it, you’ve got to be able to understand it. It looks as if you may not have represented your knowledge correctly (or just didn’t completely nail down that particular piece of knowledge) because I see at least one error in the part where you had to identify assumptions that would need to be satisfied. It could also be that you didn’t completely understand these assumptions, or how to apply them because when I look at your DAA and worksheet, I see at least one case where you misidentified whether an assumption was satisfied in the data set with which you were working. Just so you know what all of the correct answers were, let me list them out. The assumptions that have to be met when conducting a t-test are: Independence of observations; Outcome (or dependent) variable is quantitative and normally distributed; and Homogeneity of variance. Of these, only the first and third were met in this data set. So, all in all, I think you may want to dig back into the materials a bit. It looks as if you may not have represented your knowledge correctly (or just didn’t completely nail down that particular piece of knowledge) because I see at least one error in the part where you had to identify assumptions that would need to be satisfied. It could also be that you didn’t completely understand these assumptions, or how to apply them because when I look at your DAA and worksheet, I see at least one case where you misidentified whether an assumption was satisfied in the data set with which you were working. Just so you know what all of the correct answers were, let me list them out. The assumptions that have to be met when conducting a t-test are: Independence of observations; Outcome (or dependent) variable is quantitative and normally distributed; and Homogeneity of variance. Of these, only the first and third were met in this data set. So, all in all, I think you may want to dig back into the materials a bit.
Please select a choice 0.50 0.00 0 1 3 3 Please select a choice Please select a choice 0 Is there a difference in GPA between male and female students? 4 In the fourth segment of the rubric, you had to come up with a research question, hypotheses and alpha level. 5 As for p-value, well, we know that p-value is what we’ve been chasing, right? Unfortunately, it doesn’t appear to be correct in your assignment submission. Please check to see that you copied it correctly from the SPSS output. Also, keep in mind that since the Levene test was found to be non-significant, we can use the “equal variance assumed” row I provided a hint in the worksheet itself about this (you couldn’t miss it — it’s in a big red box). Let’s continue on to t-tests, your understanding of which is evaluated in the 5th segment of the scoring rubric for this unit. Remember that a t-test is all about determining whether the means of 2 groups are different in a statistically significant way (meaning that they’re different but not simply because you sampled in a certain way but because if you kept sampling over and over, you’d see the same kind of effect). To get to a p-value which helps you understand whether you are indeed looking at a statistically significant difference, you’ve got to calculate some other statistics, as well. As for p-value, well, we know that p-value is what we’ve been chasing, right? Unfortunately, it doesn’t appear to be correct in your assignment submission. Please check to see that you copied it correctly from the SPSS output. Also, keep in mind that since the Levene test was found to be non-significant, we can use the “equal variance assumed” row I provided a hint in the worksheet itself about this (you couldn’t miss it — it’s in a big red box). Onto confidence intervals: We learned a unit or two ago that confidence intervals help us understand the range of numbers within which a given parameter of interest probably lies. In this part of the assignment, you had to specify the lower and upper bounds of that range, and the SPSS output should have come to your rescue and provided you the 95% confidence interval for the difference between the 2 means. Since we are assuming equal variance here (because Levene’s test was non-significant), the lower and upper bound numbers should have been offered in the first row of the results. Something went wrong here so I would revisit the material, and maybe re-run this in SPSS to see whether you get different results. As for p-value, well, we know that p-value is what we’ve been chasing, right? Unfortunately, it doesn’t appear to be correct in your assignment submission. Please check to see that you copied it correctly from the SPSS output. Also, keep in mind that since the Levene test was found to be non-significant, we can use the “equal variance assumed” row I provided a hint in the worksheet itself about this (you couldn’t miss it — it’s in a big red box). 5 5 0 0 5 mean diff As I glance down your paper, I see some problems in what should be simple transcription of descriptive statistics from SPSS output. It looks as if the following aren’t right: Please select a choice 0 Yes 5 So, either you made a mistake when you copied the numbers (or filled out the worksheet; note that if the numbers appear as correct in at least one of those formats, you received partial credit), OR you may not have followed carefully enough the step-by-step SPSS guide. 5 mean for females; mean for males; 5 standard deviation for females; 5 0 1 5 0 0 5 What is the main strength of a t-test? Both of your answers were incorrect, so I’m not sure what happened here. You might just want to check out the course material and get this moving in the right direction again. The last section where you had to evaluate the strength and limitation of a t-test is another of those you-either-know-it,-or-you-don’t kinds of situations. Both of your answers were incorrect, so I’m not sure what happened here. You might just want to check out the course material and get this moving in the right direction again. What is the main limitation of a t-test? It can evaluate whether the sample size needs to be larger. Put an “X” in Col H to describe quality of DAA writing >SPECIAL WORKSHEET u 9a 0 Please select a choice 0 0 Please select a choice Please select a choice 0 0 Please select a choice 0 ‘ for each assumption that needs to be satisfied when conducting the main test (the ONE-WAY ANOVA) featured in the article
Please select a choice 0 Please select a choice 0 Please select a choice 0 Please select a choice 0 Please select a choice 0 Please select a choice 0 Please select a choice 0 0 Please select a choice 0 0 Please select a choice 0 0 Please select a choice 0 plicitly stated. If you get stuck, just list the typical alpha level and you’ll be right!)
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Please select a choice 0 Please select a choice 0 Please select a choice 1 Please select a choice 1 SPECIAL REQUIRED WORKSHEET FOR U09A1 – Journal Article Assignment other DAA form or template is required. 2 other important notes: Section 1 – DATA CONTEXT: In this section, you’ll be making choices from drop-down menus. Remember that even though the article talks about gender as a variable, for example, we are not looking at that in this assignment. We are ONLY LOOKING at the main test in the article: the ONE-WAY ANOVA. If you’re not sure what I’m talking about, you should be able to figure it out from the article itself. If you still can’t, then please note the variables below. Those should help. Section 2 – TESTING ASSUMPTIONS: In this section, you’ll be using drop-down menus to choose ‘yes’ or ‘no’. Please note that the article does not talk about the assumptions of a ONE-WAY ANOVA (which is, of course, the main test used in the article). You’ll have to call upon your own learning from the course materials (and beyond) to identify the testing assumptions here. Section 3 – RESEARCH QUESTION, HYPOTHESES, AND ALPHA LEVEL: In this section, you’ll be using drop-down menus. REMINDER: We are analyzing the main One-Way ANOVA in the study, the one that relates the variables specified in Section 1. Section – RESULTS AND INTERPRETATION: In this section, you’ll be using drop-down menus and you’ll be filling in the blanks. Remember that you’re only evaluating the main One-Way ANOVA in the article. If you’re not sure what that is, please see instructions all the way at the top of this worksheet. Section 5 – CONCLUSION: In this section, you’ll be using drop-down menus
1 x or , so you know what? I took both! If you were able to understand that we were dealing with a quantitative variable, then you were on the right track so I gave you credit. But something must have gone wrong because I noticed you misidentified at least one of these scales of measurement. I would take a look at the feedback I just provided, study the variable types again, and see if you can make sure these concepts are yours.
2 0% Please select a choice 0 0 Scale of measurement for one of these variables could be tricky, which is why I gave full credit for reasonable answers. That said, there were some unreasonable ones among your choices, so you did have to think this through and figure out which would be reasonable, particularly for the Reading Comprehension variable. The “Presence of Music” variable was fairly straightforward: That had to be nominal. No, it can’t be ordinal. If you have any doubt of this, just check out a number of Web sites that list “yes / no” as a nominal variable (what I’m trying to hint at here is that if you understood that “Presence of Music” has the values of “yes” or “no,” then this was a fairly straightforward scale of measurement to knock out). I also pushed hard in my comments on previous work to make sure you understood the predictor for a t-test as a nominal variable (see? There’s always method to the madness). As for Reading Comprehension, that was the tricky one. I could see arguments for Ratio or Interval, so you know what? I took both! If you were able to understand that we were dealing with a quantitative variable, then you were on the right track so I gave you credit. But something must have gone wrong because I noticed you misidentified at least one of these scales of measurement. I would take a look at the feedback I just provided, study the variable types again, and see if you can make sure these concepts are yours. Hi , or Ratio or Interval
0 0 0% 15% at 5 pm CST. Both a worksheet AND a Word doc (DAA) are required for this one. I’ve posted the worksheet in Updates / Handouts, so you’re free to get started on it. No Please select a choice 20% Predictor (or Independent) variable 0 0% 10% Please select a choice Outcome (or Dependent) Variable 10% Nominal Ordinal Ratio Scale of measurement for one of these variables could be tricky, which is why I gave full credit for reasonable answers. That said, there were some unreasonable ones among your choices, so you did have to think this through and figure out which would be reasonable, particularly for the Reading Comprehension variable. The “Presence of Music” variable was fairly straightforward: That had to be nominal. No, it can’t be ordinal. If you have any doubt of this, just check out a number of Web sites that list “yes / no” as a nominal variable (what I’m trying to hint at here is that if you understood that “Presence of Music” has the values of “yes” or “no,” then this was a fairly straightforward scale of measurement to knock out). I also pushed hard in my comments on previous work to make sure you understood the predictor for a t-test as a nominal variable (see? There’s always method to the madness). As for Reading Comprehension, that was the tricky one. I could see arguments for Ratio or Interval, so you know what? I took both! If you were able to understand that we were dealing with a quantitative variable, then you were on the right track so I gave you credit. But something must have gone wrong because I noticed you misidentified at least one of these scales of measurement. I would take a look at the feedback I just provided, study the variable types again, and see if you can make sure these concepts are yours. ), p-value (.001), and Degrees of freedom were plainly spelled out in the article. How plainly were they spelled out? Pretty much as I spelled them out in the worksheet. As for effect size (0.61), I pointed you to the table. All you had to do was pull the right effect size from the article, compare it to that table, and then look through the answer choices in the worksheet. The answer was literally in the question. Finally, as for the question about whether the null should have been rejected (answer = yes), that should have been feasible to figure out IF you understand how null hypothesis testing works, if you’d studied the article and understood it, and if you’d worked to understand the principles of one-way ANOVA. Those are a lot of IFs so if they didn’t all come together, please jump on them now before you hit the next assignment. My review of your worksheet shows at least one thing went wrong in this section, so I would do some review.
” and the limitation should have been, “ ” If you’re in doubt, just check the article. The main conclusion could be derived with a little bit of logic grounded in the work you did in the null hypothesis testing section of the assignment, combined with a good reading of the article. I did see at least one incorrect answer in this section, so you might want to backtrack and see where you might have been misled.
Onward and upward — one assignment to go — this one, as you know, is due June 17 at 5 pm CST. Both a worksheet AND a Word doc (DAA) are required for this one. I’ve posted the worksheet in Updates / Handouts, so you’re free to get started on it. Interval Please select a choice Please select a choice 0 There is an effect of reading comprehension on math skills in jr. high school students. There is no effect of lyrical music on reading comprehension for jr. high school students. 1
1 0 Please select a choice 0 Please select a choice Please select a choice It cannot evaluate the means between more than 2 groups. It can evaluate whether there’s a statistically significant difference between 2 groups. It can predict the required sample size for a follow-up study. 0 Gender correlates with the previous GPA. 0.50 0.00 Please select a choice GPA/Final Please select a choice Please select a choice Please select a choice Please select a choice It made use of a population that isn’t well represented in the literature. All of the above. It can evaluate whether the sample size needs to be larger. Please select a choice
2
ENTER NAME HERE—>
0
When you submit your work, will you include a histogram of QUIZ
3
Please select a choice
1
When you submit your work, will you include a descriptive statistics table for QUIZ3 (collapsed across the 3 sections)?
When you submit your work, will you include the SPSS output for the Shapiro-Wilk test?
Please select a choice 0
When you submit your work, will you include the SPSS output for the Levene test?
When you submit your work, will you include the SPSS output for the
mean
When you submit your work, will you include a descriptive statistics table for QUIZ3, broken down by section?
When you submit your work, will you include the SPSS output for the results of the ANOVA test?
When you submit your work, will you include the SPSS output for multiple comparisons (Tukey test)?
Variable
What kind of Variable Is This?
What is the Scale of the Variable?
SECTIONS =
QUIZ3 =
What is the overall sample size?
Assumptions
Select ‘
Yes
Select ‘Yes’ for each assumption that was satisfied in the data set you’re working with
No
Independence of observations
Outcome (or dependent) variable is quantitative and normally distributed
Homogeneity of variance
Variables are linearly related
The numbers look pretty in pink font
Presence of bivariate outliers
To evaluate these assumptions, please fill in the blanks with the results of the following tests:
Shapiro-Wilk Test, Statistic =
<-------- Use THREE decimal places
Shapiro-Wilk Test,
p-value =
Levene’s Test, Statistic (F-value) =
Levene’s Test, p-value =
Articulate a research question relevant to the statistical test
Articulate the null hypothesis
Articulate the alternative hypothesis
Specify the alpha level
ANOVA: Fill in the blanks to report means and standard deviations for each level of the factor in the ANOVA.
Mean
Standard Deviation
Section 1
Section 2
Section 3
Fill in the blanks to report the results from the ANOVA you conducted.
Degrees of freedom, Between-Groups =
Degrees of freedom, Within-Groups =
F-value =
p-value = 0
effect size (eta2) =
For the ne
x
Based on the results of the ANOVA, should the null hypothesis be rejected?
Based on the results of the ANOVA, should the post-hoc test (Tukey HSD) be performed?
If you decide to conduct the Tukey HSD post-hoc test, please report your results here (fill in the blanks and use a drop-down menu):
Section 1 vs. Section 2
Mean difference =
p-level =
Is the comparison significant?
Section 1 vs. Section 3
p-level = 0
Is the comparison significant? Please select a choice 0
Section 2 vs. Section 3
p-level = 0
Is the comparison significant? Please select a choice 0
What is the main strength of a one-way ANOVA?
What is the main limitation of a one-way ANOVA?
Ready to begin? So far, no questions have been answered.
This worksheet is absolutely positively required. Why? It compels you to engage with each question and will guide your efforts on the long-form Word doc part of the assignment. What’s in it for you? Points. Lots of them. Remember: This worksheet is required but does not replace your fully-written DAA (Word doc). You must submit BOTH.
4
5
OUTPUT
SCORING
great job on DAA
First off, you did a great job of working through the DAA. You’ve produced a compelling narrative that stands on its own, about an exercise in one-way ANOVA. This DAA demonstrates real engagement with the concepts. When I read your DAA, I can SEE the learning you did. This is well done, indeed.
1
7
ENTER NAME HERE—> 0
okay job – hit all the basics
First off, let me say this: You did a fine job across the DAA. You hit the essential points concisely and I have no doubt you worked hard on this. Still, a bit more clarification and elaboration would have helped demonstrate your mastery. The other advantage to additional explanation if that if you produce an incorrect answer, the elaboration can showcase your reasoning which, if correct, could win you extra points.
okay job with effort
First off, let me say this: Your DAA made me proud. Did you have a firm grasp of ALL the concepts and materials? No. But did you try really, sincerely, and truly hard to grasp those concepts and show me you were trying? Oh yeah! Wow – you gave this a LOT of effort. Some of it came together well and some of it could use some additional work, some clarification and elaboration.
Rubric #
RAW SCORE
WEIGHTED
not so good job
First off, you invested some effort in developing this DAA. That’s a good start. Getting beyond that start is the key, of course, but we’ve got to start from a platform of making an attempt to get this right, and that platform can be found for sure in this DAA. Where are the gaps? I would say that all of the gaps fall into a few big buckets: (1) Your representation of the concepts wasn’t always consistent with the materials; (2) You didn’t provide a whole lot of explanation, clarification, and elaboration; (3) You didn’t address all of the requirements. Note that I don’t have the discretion to overlook those things. Those things are required by the rubric. I did my best to get you the best outcome but the rubric ultimately has the last word.
0%
20%
writing and grammar
One (other) note about the DAA: Some of the concepts were probably a lot more accurate in your mind than they appeared on your paper. No, I can’t read your mind or anything – I’m not saying that. I’m just saying that when I read your DAA, I get the sense that you had a much firmer grasp of the concepts than your writing would have me to believe. For one thing, some of what you’re saying isn’t entirely clear. With some clarification and elaboration, it could definitely get there but right now, I’m not sure whether you really grasped the concepts or whether you’re kind of talking around them, so to speak. The other thing you should definitely consider is working on the proofreading. I found a number of grammar problems.
10%
Predictor variable
3
2
5%
Outcome variable
4 0% 10% 0%
Nominal
Moderator variable
5
9%
2%
Ratio
Mediator variable
6
Interval
7
100%
Continuous
Ellipticular
Are there significant differences between Quiz 3 grades among the 3 sections?
Are there significant differences between Quiz 3 grades among men and women?
Detailed Comments on Your Assignment:
What is the relationship between socioeconomic status and Quiz 3 grades?
Hi,
Super-amazing job!!! Wow!!! What an accomplishment!
This is the best kind of proof that hard work and determination pay off.
This was not an easy assignment. It pretends to be about one-way ANOVAs but it’s about a whole lot more. Everything you’ve learned appears in this assignment and it challenges learners to bring all the concepts and techniques together. So, what I was looking for here is how well you were able to do that, and from what I can tell, you did that REALLY well!
Here are my comments:
Section 2 of the Rubric: This one asked you all the standard stuff about the variables you’re using in this analysis. Why is this important? We’ve got to know what we’re examining when we do a research study, and how we would go about measuring those things.
105
Section 3 of the Rubric: You may be thinking, “Why do I have to wrestle with these assumptions again? I already went through this with the t-test assignment.” Well, if you recognized that the assumptions of an ANOVA are the same as those for a t-test, then you are right! You did go through this already. But it’s important that we consider these with respect to ANOVAs.
I noticed more than 2 problems in the assumptions part of the assignment. Here’s how that section should have looked: When asked to indicate which assumptions need to be satisfied to conduct an ANOVA, the correct answers were independence of observations, outcome (or dependent) variable is quantitative and normally distributed, and homogeneity of variables. Everything else didn’t have to be satisfied. When asked to evaluate whether or not these assumptions had been satisfied in the data set with which you were working, the answer is yes for everything except the one saying that the DV has to be quantitative and normally distributed.
As for the Shapiro-Wilk test and Levene’s test, 3 of the items did not appear to be right. You may want to go back to the course materials and see what happened.
Section 4 of the Rubric: This is an area where we’ve all had a good chance to practice during the course. Hypothesis testing is core to what we do as researchers. Even if we don’t intend to do any research beyond our experience at Capella, this sort of training will make us better critical thinkers, which is certainly useful across professions.
I could see from your assignment submissions that you made at least one error here. I’d revisit the course materials and get some more practice with the conceptual framework underlying hypothesis testing.
Section 5: The previous sections were mostly aimed at seeing whether you understood the basic principles of ANOVAs. This section is focused on evaluating how well you can actually do one.
As it turns out, you may need to do some work in this area because I detected a bunch of errors in your reporting of means and standard deviations. It could be that something went wrong when you attempted to generate the output or it could be something conceptual. Either way, it’s worth taking a few steps back and retracing your steps.
Now I did see some errors in your reporting of the statistics that are at the core of this assignment, namely, the ones that help us understand the results of the ANOVA you conducted. Specifically, I could see the following items aren’t consistent with what you were supposed to be reporting:
Between-Groups Degrees of Freedom,
Within-Groups Degrees of Freedom,
F-value,
Let’s turn now to the interpretive piece. Based on your ANOVA results, the null hypothesis should indeed be rejected and the post-hoc test should be performed. At least one of your answers differed from this so I think it’s worth diving back into the ANOVA material and getting a sense of how to interpret your ANOVA findings.
Finally, in the section asking you to report the results of your Tukey HSD test, over a third of the items were incorrect. The specific items include the following:
Section 1 vs. Section 2 –
Mean difference,
p-level,
Section 1 vs. Section 3 –
Section 2 vs. Section 3 –
Section 6: Here you had to address strengths and limitations. You scored at least one wrong here so I would check out how this happened and make sure you’ve got a lock on it.
Thanks for all the amazing hard work and dedication over the quarter.
-Dr. Reynolds
Does age correlate with Quiz 3 grades for the 3 sections?
When you submit your work, will you include a histogram of QUIZ3?
Please select a choice
Please select a choice 0 1
There is no difference between Quiz 3 grades in the 3 sections.
There is no difference between grades received on quiz3 based on one’s gender.
When you submit your work, will you include a descriptive statistics table for QUIZ3 (collapsed across the 3 sections)?
SES has no impact on grades received for quiz3.
Please select a choice 0 1
AMAZING
Wow!!! Just wow!!!!
You did an amazing job through and through.
I give out very few 100s on this assignment. Why? Well, you’d have to have gotten everything (or almost everything) right and shown that you understand why you got everything right. It doesn’t happen very often. A lot of learners have a good deal of difficulty with this assignment.
And then your DAA (and worksheet) come along, demonstrating the conceptual mastery necessary for you to proclaim victory far and wide.
I was honestly super-impressed with your DAA. Not only did it make well-supported arguments demonstrating understanding, but it also explored those concepts in a way that speaks very highly of your command of the work for this unit. As an example, your Interpretation section made it clear that you’d grappled with what we can learn from a one-way ANOVA. REALLY WELL DONE!
CONGRATULATIONS ON A SUPER-AMAZING ACHIEVEMENT!
-Dr. Reynolds
There is a difference between the grades received on quiz3 in the 3 sections.
There is a difference between the grades received on quiz3 in 3 sections.
x
Great job
Super-amazing job!!! Wow!!! What an accomplishment!
This is the best kind of proof that hard work and determination pay off.
This was not an easy assignment. It pretends to be about one-way ANOVAs but it’s about a whole lot more. Everything you’ve learned appears in this assignment and it challenges learners to bring all the concepts and techniques together. So, what I was looking for here is how well you were able to do that, and from what I can tell, you did that REALLY well!
Here are my comments:
Hi,
Super-amazing job!!! Wow!!! What an accomplishment!
This is the best kind of proof that hard work and determination pay off.
This was not an easy assignment. It pretends to be about one-way ANOVAs but it’s about a whole lot more. Everything you’ve learned appears in this assignment and it challenges learners to bring all the concepts and techniques together. So, what I was looking for here is how well you were able to do that, and from what I can tell, you did that REALLY well!
Here are my comments:
Please select a choice
When you submit your work, will you include the SPSS output for the Shapiro-Wilk test?
Great effort
Hi,
Great job, overall! This was not an easy assignment. It pretends to be about one-way ANOVAs but it’s about a whole lot more. Everything you’ve learned appears in this assignment and it challenges learners to bring all the concepts and techniques together. So, what I’m looking for here is how well you were able to do that.
While that may seem like an overwhelming challenge, it’s actually good. It means that if I saw you were able to grasp hypothesis testing, for example, but not post-hoc testing, I made sure you were rewarded for what you had indeed grasped.
And you were rewarded. You’ll see sections of this assignment where maybe you didn’t do as well as you’d hoped (in terms of the # of answers marked incorrect), but where you nonetheless scored way better on the rubric than would have been otherwise justified.
Here are some additional comments:
Please select a choice 0 1
Good effort
Hi,
This was not an easy assignment. It pretends to be about one-way ANOVAs but it’s about a whole lot more. Everything you’ve learned appears in this assignment and it challenges learners to bring all the concepts and techniques together. So, what I’m looking for here is how well you were able to do that.
While that may seem like an overwhelming challenge, it’s actually good. It means that if I saw you were able to grasp hypothesis testing, for example, but not post-hoc testing, I made sure you were rewarded for what you had indeed grasped.
And you were rewarded. You’ll see sections of this assignment where maybe you didn’t do as well as you’d hoped (in terms of the # of answers marked incorrect), but where you nonetheless scored way better on the rubric than would have been otherwise justified.
Here are some more comments:
35
There is a difference between Quiz 3 grades in the 3 sections.
420
There is a difference between grades received on quiz3 based on one’s gender.
When you submit your work, will you include the SPSS output for the Levene test?
Thanks for all the amazing hard work and dedication over the quarter.
-Dr. Reynolds
Unknown
SES has an impact on grades received for quiz3.
Please select a choice 0 1
There is no difference between the grades received on quiz3 in the 3 sections.
When you submit your work, will you include the SPSS output for the means plot? Please select a choice Please select a choice
Please select a choice 0 1 Yes
It allows for comparison of more than 2 groups in one test, avoiding increased risk of Type I error.
No
It allows for comparison between 2 groups only.
When you submit your work, will you include a descriptive statistics table for QUIZ3, broken down by section?
Not Applicable
It allows for multiple changes in research design after the study has commenced.
Please select a choice 0
It allows for green kryptonite resistance (but not red).
Please select a choice 0 Please select a choice Please select a choice
Does the previous GPA correlate with the number of correct final exam scores?
A statistically significant result does not tell us which groups show statistically significant differences.
When you submit your work, will you include the SPSS output for multiple comparisons (Tukey test)?
Does gender correlate with previous GPA?
A statistically significant result indicates that the study was not conducted properly.
Please select a choice 0
sec2
You did pretty well on this. I only saw one error here. Just so you know, Sections 3 should be a nominal predictor variable, while Quiz3 should be a ratio outcome variable. The sample size should be 105.
More than one thing went wrong here if I’m reading your worksheet and full-length paper correctly. Just so you know, Sections 3 should be a nominal predictor variable, while Quiz3 should be a ratio outcome variable, with the sample size equal to 105. I’d check to see specifically where things got a little derailed in this part of the assignment, and then consult the course materials as needed to nail this down. You’ll need these skills as you continue along in your academic journey, so it’s worth buttoning them up now.
Section 2 of the Rubric: This one asked you all the standard stuff about the variables you’re using in this analysis. Why is this important? We’ve got to know what we’re examining when we do a research study, and how we would go about measuring those things. More than one thing went wrong here if I’m reading your worksheet and full-length paper correctly. Just so you know, Sections 3 should be a nominal predictor variable, while Quiz3 should be a ratio outcome variable, with the sample size equal to 105. I’d check to see specifically where things got a little derailed in this part of the assignment, and then consult the course materials as needed to nail this down. You’ll need these skills as you continue along in your academic journey, so it’s worth buttoning them up now.
Do the final exam scores correlate with the geographical areas?
A statistically significant result means a t-test should have been performed, not an ANOVA.
Does socioeconomic status correlate with the final exam scores?
It cannot provide the 1.21 jigowatts necessary for time travel.
sec3
You must have had a good handle on this section because I noticed only one or two problems. Here’s how that section should have looked: When asked to indicate which assumptions need to be satisfied to conduct an ANOVA, the correct answers were independence of observations, outcome (or dependent) variable is quantitative and normally distributed, and homogeneity of variables. Everything else didn’t have to be satisfied. When asked to evaluate whether or not these assumptions had been satisfied in the data set with which you were working, the answer is yes for everything except the one saying that the DV has to be quantitative and normally distributed.
As for the Shapiro-Wilk test and Levene’s test, 3 of the items did not appear to be right. You may want to go back to the course materials and see what happened.
Section 3 of the Rubric: You may be thinking, “Why do I have to wrestle with these assumptions again? I already went through this with the t-test assignment.” Well, if you recognized that the assumptions of an ANOVA are the same as those for a t-test, then you are right! You did go through this already. But it’s important that we consider these with respect to ANOVAs. I noticed more than 2 problems in the assumptions part of the assignment. Here’s how that section should have looked: When asked to indicate which assumptions need to be satisfied to conduct an ANOVA, the correct answers were independence of observations, outcome (or dependent) variable is quantitative and normally distributed, and homogeneity of variables. Everything else didn’t have to be satisfied. When asked to evaluate whether or not these assumptions had been satisfied in the data set with which you were working, the answer is yes for everything except the one saying that the DV has to be quantitative and normally distributed.
As for the Shapiro-Wilk test and Levene’s test, 3 of the items did not appear to be right. You may want to go back to the course materials and see what happened.Section 3 of the Rubric: You may be thinking, “Why do I have to wrestle with these assumptions again? I already went through this with the t-test assignment.” Well, if you recognized that the assumptions of an ANOVA are the same as those for a t-test, then you are right! You did go through this already. But it’s important that we consider these with respect to ANOVAs. I noticed more than 2 problems in the assumptions part of the assignment. Here’s how that section should have looked: When asked to indicate which assumptions need to be satisfied to conduct an ANOVA, the correct answers were independence of observations, outcome (or dependent) variable is quantitative and normally distributed, and homogeneity of variables. Everything else didn’t have to be satisfied. When asked to evaluate whether or not these assumptions had been satisfied in the data set with which you were working, the answer is yes for everything except the one saying that the DV has to be quantitative and normally distributed.
As for the Shapiro-Wilk test and Levene’s test, 3 of the items did not appear to be right. You may want to go back to the course materials and see what happened.
Please select a choice
nullhyp
sec4
Section 4 of the Rubric: This is an area where we’ve all had a good chance to practice during the course. Hypothesis testing is core to what we do as researchers. Even if we don’t intend to do any research beyond our experience at Capella, this sort of training will make us better critical thinkers, which is certainly useful across professions. I could see from your assignment submissions that you made at least one error here. I’d revisit the course materials and get some more practice with the conceptual framework underlying hypothesis testing. Section 4 of the Rubric: This is an area where we’ve all had a good chance to practice during the course. Hypothesis testing is core to what we do as researchers. Even if we don’t intend to do any research beyond our experience at Capella, this sort of training will make us better critical thinkers, which is certainly useful across professions. I could see from your assignment submissions that you made at least one error here. I’d revisit the course materials and get some more practice with the conceptual framework underlying hypothesis testing.
Previous GPA does not correlate with the number of correct final exam scores.
Gender does not correlate with the previous GPA.
The previous GPA correlates with the number of correct final exam scores.
sec5
It looks as if you can! I see only one or two errors in your reporting of means and standard deviations.
Now I did see some errors in your reporting of the statistics that are at the core of this assignment, namely, the ones that help us understand the results of the ANOVA you conducted. Specifically, I could see the following items aren’t consistent with what you were supposed to be reporting: Between-Groups Degrees of Freedom, Within-Groups Degrees of Freedom, F-value, effect size (eta2)
Finally, in the section asking you to report the results of your Tukey HSD test, only about a third of the items were incorrect. The specific items include the following:
Section 5: The previous sections were mostly aimed at seeing whether you understood the basic principles of ANOVAs. This section is focused on evaluating how well you can actually do one. As it turns out, you may need to do some work in this area because I detected a bunch of errors in your reporting of means and standard deviations. It could be that something went wrong when you attempted to generate the output or it could be something conceptual. Either way, it’s worth taking a few steps back and retracing your steps.Now I did see some errors in your reporting of the statistics that are at the core of this assignment, namely, the ones that help us understand the results of the ANOVA you conducted. Specifically, I could see the following items aren’t consistent with what you were supposed to be reporting: Between-Groups Degrees of Freedom, Within-Groups Degrees of Freedom, F-value, effect size (eta2).
Finally, in the section asking you to report the results of your Tukey HSD test, over a third of the items were incorrect. The specific items include the following: Section 1 vs. Section 2 – Mean difference, p-level, determination of whether the comparison was significant; Section 1 vs. Section 3 – Mean difference, p-level, determination of whether the comparison was significant; Section 2 vs. Section 3 – Mean difference, determination of whether the comparison was significant;
. Section 5: The previous sections were mostly aimed at seeing whether you understood the basic principles of ANOVAs. This section is focused on evaluating how well you can actually do one. As it turns out, you may need to do some work in this area because I detected a bunch of errors in your reporting of means and standard deviations. It could be that something went wrong when you attempted to generate the output or it could be something conceptual. Either way, it’s worth taking a few steps back and retracing your steps.
Now I did see some errors in your reporting of the statistics that are at the core of this assignment, namely, the ones that help us understand the results of the ANOVA you conducted. Specifically, I could see the following items aren’t consistent with what you were supposed to be reporting: Between-Groups Degrees of Freedom, Within-Groups Degrees of Freedom, F-value, effect size (eta2). Let’s turn now to the interpretive piece. Based on your ANOVA results, the null hypothesis should indeed be rejected and the post-hoc test should be performed. At least one of your answers differed from this so I think it’s worth diving back into the ANOVA material and getting a sense of how to interpret your ANOVA findings.
Finally, in the section asking you to report the results of your Tukey HSD test, over a third of the items were incorrect. The specific items include the following: Section 1 vs. Section 2 – Mean difference, p-level, determination of whether the comparison was significant; Section 1 vs. Section 3 – Mean difference, p-level, determination of whether the comparison was significant; Section 2 vs. Section 3 – Mean difference, determination of whether the comparison was significant;
.
Gender correlates with the previous GPA.
Please select a choice
althyp
sec 6
Select from drop-down menu boxes
The previous GPA does not correlate with the number of correct final exam scores.
Variable What kind of Variable Is This? What is the Scale of the Variable?
SECTIONS = Please select a choice Please select a choice 0 0 2 Please select a choice
QUIZ3 = Please select a choice Please select a choice 0 0 2
0.50
0.00
0.05
Gender/GPA
What is the overall sample size? Please select a choice 0 2
Gender/Final
0.90
Gender/Total
GPA/Final
GPA/Total
Final/Total
Assumptions
Select ‘Yes’ for each assumption that needs to be satisfied when conducting a t-test
Independence of observations Please select a choice Please select a choice 0 0 Yes Yes 3 Gender/Final
Outcome (or dependent) variable is quantitative and normally distributed Please select a choice Please select a choice 0 0 Yes No 3 GPA/Final
Homogeneity of variance Please select a choice Please select a choice 0 0 Yes Yes 3 GPA/Total
Variables are linearly related Please select a choice Please select a choice 0 1 3 Final/Total
The numbers look pretty in pink font Please select a choice Please select a choice 0 1 3
Presence of bivariate outliers Please select a choice Please select a choice 0 1 3
3
Shapiro-Wilk Test Statistic
0.948
Shapiro-Wilk Test Statistic,
Shapiro-Wilk Test p-level
Levene’s Test Statistic (F-value)
2.898
Levene’s Test Statistic (F-value),
Levene’s Test p-level
0.06
Levene’s Test p-level,
Shapiro-Wilk Test Statistic, Levene’s Test Statistic (F-value), Levene’s Test p-level
Articulate a research question relevant to the statistical test Please select a choice 0 Are there significant differences between Quiz 3 grades among the 3 sections? 4
Articulate the null hypothesis Please select a choice 0 There is no difference between Quiz 3 grades in the 3 sections. 4
Articulate the alternative hypothesis Please select a choice 0 There is a difference between Quiz 3 grades in the 3 sections. 4
Specify the alpha level Please select a choice 0 0.05 4
mean
std
Section 1 0.00 0 0 0
7.27
1.153
Section 2 0.00 0 0 0
6.33
1.611
Section 3 0.00 0 0 0
7.94
1.56
5
Between-Groups Degrees of Freedom, 0 0 2 5 Between-Groups Degrees of Freedom,
Within-Groups Degrees of Freedom, 0 0
102
F-value,
0.000
10.951
p-value,
effect size (eta2),
0.17676124
Between-Groups Degrees of Freedom, Within-Groups Degrees of Freedom, F-value, effect size (eta2)
Based on the results of the ANOVA, should the hypothesis be rejected?
Based on the results of the ANOVA, should the post-hoc test (Tukey HSD) be performed? Please select a choice 0
The last section where you had to evaluate the strength and limitation of a t-test is another of those you-either-know-it,-or-you-don’t kinds of situations.
One of your answers here is incorrect, so I would check out the material and see where things didn’t go the way they should have.
Both of your answers were incorrect, so I’m not sure what happened here. You might just want to check out the course material and get this moving in the right direction again.
The last section where you had to evaluate the strength and limitation of a t-test is another of those you-either-know-it,-or-you-don’t kinds of situations. Both of your answers were incorrect, so I’m not sure what happened here. You might just want to check out the course material and get this moving in the right direction again.
Section 1 vs. Section 2 5 Section 1 vs. Section 2 –
Mean difference, 0 0
0.939
p-level, 0 0
0.021
determination of whether the comparison was significant,
Section 1 vs. Section 2 – Mean difference, p-level, determination of whether the comparison was significant, ;
Section 1 vs. Section 3 Section 1 vs. Section 3 Section 1 vs. Section 3 –
Mean difference, 0 0
-0.667
p-level, 0 0
0.159
determination of whether the comparison was significant, Please select a choice 0 No determination of whether the comparison was significant,
6
Section 1 vs. Section 3 – Mean difference, p-level, determination of whether the comparison was significant, ;
Section 2 vs. Section 3 Section 2 vs. Section 3 Section 2 vs. Section 3 –
Mean difference, 0 0
-1.606
strongcorr
p-level, 0 1 0
Strong positive
determination of whether the comparison was significant, Please select a choice 0 Yes determination of whether the comparison was significant,
Strong negative
Section 2 vs. Section 3 – Mean difference, determination of whether the comparison was significant, ;
Weak negative
Weak positive
Please select a choice
evallp
It can evaluate whether there is a relationship between 2 variables.
It can evaluate whether one of the variables causes another variable.
It can evaluate whether the sample size needs to be larger.
What is the main strength of a one way anova
It can evaluate whether there is a relationship between homoscedacity and homogeneity.
Please select a choice 0 It allows for comparison of more than 2 groups in one test, avoiding increased risk of Type I error.
Please select a choice
astudio
What is the main limitation of a one way anova?
It cannot evaluate whether there is a relationship between 2 variables.
Please select a choice 0 A statistically significant result does not tell us which groups show statistically significant differences.
It cannot evaluate whether one of the variables causes another variable.
It can evaluate whether there is a relationship between homoscedacity and homogeneity.
Journal Article Summary
Section 1: Data File Description
Section 3: Research Question, Hypotheses, and Alpha Level
Section 4: Interpretation
Section 5: Conclusion
References
2
0
1
ENTER NAME HERE—>
When you submit your work, will you include a histogram on GPA?
Please select a choice
When you submit your work, will you include a descriptive statistics table for GPA (including skew and kurtosis)?
When you submit your work, will you include the SPSS output for the Shapiro-Wilk test?
Please select a choice 0
When you submit your work, will you include the SPSS output for the Levene’s test?
When you submit your work, will you include the SPSS output for the results of the t-test?
Variable
What kind of Variable Is This?
What is the Scale of the Variable?
GENDER =
GPA =
What is the overall sample size?
Assumptions
Select ‘
Yes
Select ‘Yes’ for each assumption that was satisfied in the data set you’re working with
No
Independence of observations
Outcome (or dependent) variable is quantitative and normally distributed
Homogeneity of variance
Variables are linearly related
To evaluate these assumptions, please fill in the blanks with the results of the following tests:
Shapiro-Wilk Test,
Statistic
<-------- Use THREE decimal places
Shapiro-Wilk Test,
p-value
Levene’s Test,
Statistic (F-value)
Levene’s Test,
p-value =
Articulate a
research q
Articulate the null hypothesis
Articulate the alternative hypothesis
Specify the alpha level
t-test: Please fill in the blanks:
degrees of freedom =
t-value =
p-value = <-------- Use THREE decimal places 0
effect size (calculate this: eta2) =
For the ne
x
Based on the results of the t-test, should the null hypothesis be rejected?
Descriptive statistics for FEMALES
Mean =
<-------- Use TWO decimal places
Standard Deviation =
Descriptive Statistics for MALES
Mean difference between the means for males and females =
Please enter the LOWER and UPPER bounds of the 9
5
Lower =
Upper =
<-------- Use ONE decimal place
What is the main strength of a t-test?
What is the main limitation of a t-test?
Hold on! You’re not done. You still have
4
(and your name is one of them)
This worksheet is absolutely positively required. Why? It compels you to engage with each question and will guide your efforts on the long-form Word doc part of the assignment. What’s in it for you? Hints and points. Lots of them. Failing assignment submissions become passes. C’s turn to B’s. B’s turn to A’s. So, please hand this in. Remember: This worksheet is required but does not replace your fully-written u08a1 DAA Word doc. You must submit BOTH.
3
(2) To calculate effect size, square the t-value, then divide that by
the sum of the square of the t-value and degrees of freedomOUTPUT
SCORING
RUBRIC
1
2%
ENTER NAME HERE—> 0
Great job
Important Note: Your DAA was beautifully comprehensive. As I read through it, I got the sense that you’d really absorbed these concepts! This is an extraordinary achievement for such relatively short engagement with the concepts and materials. I am TRULY impressed! Well done!
A mediocre job on DAA – some explanation but could benefit from more
Your DAA flowed from start to finish with learning. Could it have benefited from a bit more explanation in places? Yes (e.g., in the section on assumptions and the interpretation). But overall, I could see the effort. Thank you for making that effort.
Rubric #
RAW SCORE
WEIGHTED
Not a good job on DAA — needs a lot more explanation
One note about the DAA: I think you’d be doing yourself (and your assignments) a huge favor by explaining and elaborating more in your DAA. The fact is that even if something goes awry in the numbers, even if you made a mistake in the way you used SPSS, it’s still possible for you to grab a few more points if you can demonstrate you knew what you were talking about. Right now I’m not seeing that in your DAA but in future assignments, that sort of explanation could help you out. By the way, the kind of explanation I’m talking about would have to be substantive, relevant, and meaningful; as you know, I read every word of every paragraph so I’ll be looking for content that really shows me you were working to absorb these concepts and make them your own.
0%
20%
some level of explanation but a lot of statements were inaccurate
You made a strong effort to explain what you were doing; thank you so much for doing that. It gives me a sense first of all, of hard you worked (and you did work hard!) but also of your level of achieved learning. I think the level of achieved learning is climbing but it hasn’t quite gotten where it needs to go. I’m guessing you felt that as you were working through the assignment. All this means is that there’s more work to be done. That’s part of the process. No worries.
10%
Predictor variable
3 0% 20% 0% Please select a choice
Outcome variable
4 0% 10% 0%
Nominal
Moderator variable
5
8%
Ordinal
Mediator variable
6
Ratio
7
100%
Interval
Continuous
Is there a difference in GPA between male and female students?
Is there a difference in GPA based on school location?
Detailed Comments on Your Assignment:
Is there a correlation between male and female students?
Hi,
How good should you feel about what you did here? SUPER-good. Yes, you’ve got some things you need to do here and there to shore up the gaps, but this is just really good work of which you should be tremendously proud.
Here are a few comments I worked up:
In section 1, you were asked to describe specific elements of the data set by describing the variables themselves. This is pretty important because if we don’t understand the variables and the sort of relationship we’d like to test, then none of this can help us answer any research questions.
I bring all this up because I noticed you had difficulty determining which variable was the predictor and / or which was the outcome. For this data set, the independent variable (or predictor) should have been GENDER and the dependent variable (or outcome) should have been GPA. I would check over your work and figure out where things went wrong.
Along these lines, I should mention you were asked to evaluate which scale of measurement we would use with the GENDER and GPA variables, respectively. I noticed an error or two here. The correct answers (just so you know, so you can compare them to what you did) for GENDER would be nominal (since gender can either be male or female) and for GPA, would be ratio or interval. Why should we care about any of this? Most of the parametric tests you’ll be learning about in this course (such as the t-test) require the dependent variable to be at least ratio. If you try to run those analyses on incompatible variables, your analysis will go kablooey (that’s a technical statistical term, you understand) fairly quickly.
The only other thing
105
Okay, so let’s tackle section 3 of the rubric, the one asking you to evaluate the assumptions that need to be satisfied before doing a t-test. This is the sort of stuff that you either know (based on your reading of the course material) or you don’t. Of course, the real challenge is that once you know it, you’ve got to be able to understand it.
It looks as if you may not have represented your knowledge correctly (or just didn’t completely nail down that particular piece of knowledge) because I see at least one error in the part where you had to identify assumptions that would need to be satisfied. It could also be that you didn’t completely understand these assumptions, or how to apply them because when I look at your DAA and worksheet, I see at least one case where you misidentified whether an assumption was satisfied in the data set with which you were working. Just so you know what all of the correct answers were, let me list them out. The assumptions that have to be met when conducting a t-test are: Independence of observations; Outcome (or dependent) variable is quantitative and normally distributed; and Homogeneity of variance. Of these, only the first and third were met in this data set. So, all in all, I think you may want to dig back into the materials a bit.
As for the Shapiro-Wilk test, you could very well be on the right track in your understanding of it, though, to be candid, I couldn’t be sure from what I saw in your assignment submissions (I saw at least one error of note skulking about in your work). Let’s take a step back. What does this test do? This test helps us determine whether the data set satisfied the assumption of normal distribution. In this case, since p<.05, the assumption of normal distribution was violated. Remember that for this sort of a test where we’re trying to establish whether assumptions have been met, we want to see statistical NON-significance. Conveniently, SPSS provides the output of the Shapiro-Wilk test for your review. I would revisit the material to see if you can get a better handle on the underlying concepts of this test.
Another important point: The Levene test is something you’ll want to get fairly comfortable with, since you will see it over and over in discussions of the assumptions of parametric tests. Again, I saw an error or two in your treatment of it in your assignment submissions so this is something you’ll want to review. Just so you know, Levene’s test helps us determine if the homogeneity of variance assumption has been met. SPSS can perform the Levene test and produces the output along with the results. Note that just as we saw with the Shapiro-Wilk test, we want Levene’s test to be non-significant (as judged by the p-level).
In the fourth segment of the rubric, you had to come up with a research question, hypotheses and alpha level.
Every good study begins with a good research question, which is why it’s so important to be able to get this right. Regrettably, your assignment showed that something went wrong here. So, let’s look at this: The research question is what the researcher would like to investigate. It is literally a question, and has to be asked with some precision of language. What does this mean? This means that the research question isn’t something we ask casually: the words have specific meanings. In this case, we were interested in whether male and female students had the same GPA, on average. The answer, therefore, has to be in the research question. Here’s what the question should look like: Does gender have an effect on GPA?
A few more notes: We didn’t have any interest in either the location of the school or students’ age. Similarly, this was a research question suitable for a t-test, not a correlation, so any question about correlation was automatically incorrect.
The null hypothesis you specified, also doesn’t appear to be quite right. Again, null hypotheses have to be right; they’re just not the sort of thing you can get sort of right. Here’s why: The null hypothesis is the opposite of what we think will happen in the study. It is a statement that we reject if p is less than the specified alpha level (typically, .05). When it comes to this assignment, we wondered whether there’s a statistically significant effect, so the null hypotheses had to be the opposite of that statement (no difference in GPA between men and women). If articulation of the null hypothesis is still unclear, I would suggest revisiting the course materials. Understanding what the null hypotheses are and how to formulate them will serve you well not only in this course, but throughout your career.
Now, turning to the alternative hypothesis, something appears to be not entirely right here. The alternative hypothesis is what we’d like to demonstrate in the study. Typically, it’s the affirmative statement of the research question. In our case here, it’s the statement that says that there is a difference between the GPA of male and female students. As with the null hypothesis, it’s super-important to be precise in the way we articulate it. Please reread the textbook (and/or other sources) to make sure you know what an alternative hypothesis is and how to postulate one.
One more thing to know for this section: The alpha level is typically set to .05. Yours wasn’t.
Let’s continue on to t-tests, your understanding of which is evaluated in the 5th segment of the scoring rubric for this unit. Remember that a t-test is all about determining whether the means of 2 groups are different in a statistically significant way (meaning that they’re different but not simply because you sampled in a certain way but because if you kept sampling over and over, you’d see the same kind of effect). To get to a p-value which helps you understand whether you are indeed looking at a statistically significant difference, you’ve got to calculate some other statistics, as well.
So, first off, I noticed an error in your calculation of the t-value, which you were supposed to take directly from SPSS output. Any kind of mistake here is due to maybe one of 2 factors:
(1) An incorrect test was performed. Please double-check the SPSS step-by-step guide.
(2) A rounding error
(3) A misunderstanding of what you were looking at
When I look both at your worksheet and the Word doc, I can see a problem with your calculation of degrees of freedom. This, too, was provided for you in the SPSS output for the independent samples t-test. If there is an error here, it’s likely because you copied the wrong number or maybe there’s some sort of rounding error. Remember that since Levene’s test was found not to be significant (we fail to reject the null hypothesis which said that equal variances are assumed), we can use the “equal variance assumed” row (I provided a hint in a red box, right on the worksheet to help you with this).
As for p-value, well, we know that p-value is what we’ve been chasing, right? Unfortunately, it doesn’t appear to be correct in your assignment submission. Please check to see that you copied it correctly from the SPSS output. Also, keep in mind that since the Levene test was found to be non-significant, we can use the “equal variance assumed” row I provided a hint in the worksheet itself about this (you couldn’t miss it — it’s in a big red box).
Effect Size: The effect size you listed is not correct. As discussed within this unit, SPSS doesn’t calculate the effect size for you. You have to compute it manually using a formula that you’ll find in your course materials. I also placed a hint about this in the worksheet. How big of a hint? Well, I did provide the formula. As for interpreting the magnitude of the effect size, Warner (2013) includes a table (5.2) that should help. The announcement I’d posted recently should have helped you with this, as well; I would review it.
0.05
As I glance down your paper, I see some problems in what should be simple transcription of descriptive statistics from SPSS output. It looks as if the following aren’t right:
mean for females;
standard deviation for females;
mean for males;
So, either you made a mistake when you copied the numbers (or filled out the worksheet; note that if the numbers appear as correct in at least one of those formats, you received partial credit), OR you may not have followed carefully enough the step-by-step SPSS guide.
As for the
mean diff
Onto confidence intervals: We learned a unit or two ago that confidence intervals help us understand the range of numbers within which a given parameter of interest probably lies. In this part of the assignment, you had to specify the lower and upper bounds of that range, and the SPSS output should have come to your rescue and provided you the 95% confidence interval for the difference between the 2 means. Since we are assuming equal variance here (because Levene’s test was non-significant), the lower and upper bound numbers should have been offered in the first row of the results. Something went wrong here so I would revisit the material, and maybe re-run this in SPSS to see whether you get different results.
The last section where you had to evaluate the strength and limitation of a t-test is another of those you-either-know-it,-or-you-don’t kinds of situations.
Both of your answers were incorrect, so I’m not sure what happened here. You might just want to check out the course material and get this moving in the right direction again.
One final thing: When I look over your DAA, I see someone who worked extraordinarily hard to think through and develop this assignment. I do not under any circumstances want you to think that just because I marked some things wrong, took off some points here and there, and wrote a lot of feedback, that you didn’t do well. I think you did REALLY well. This paper is what it looks like to work hard, and even though you may not have gotten everything as correct as you wanted to, I really truly believe with all my heart, that you scored a real victory here. Regardless of what you think about your abilities, you’re in the fight.
Thanks for all the hard work!
-Dr. Reynolds
Is there a relationship between GPA and student age?
When you submit your work, will you include a histogram on GPA? Please select a choice
Please select a choice 0 1
There is no difference in GPA between male and female students.
There is no difference in GPA based on school location.
When you submit your work, will you include a descriptive statistics table for GPA (including skew and kurtosis)?
There is a difference in GPA between male and female students.
Please select a choice 0 1
AMAZING
Hi,
This is really fantastic work! You swept through these sections and made these concepts your own. Really well done!
Just a few comments:
There is no correlation between male and female students.
x Great job Hi,
How good should you feel about what you did here? SUPER-good. Yes, you’ve got some things you need to do here and there to shore up the gaps, but this is just really good work of which you should be tremendously proud.
Here are a few comments I worked up:
Hi,
How good should you feel about what you did here? SUPER-good. Yes, you’ve got some things you need to do here and there to shore up the gaps, but this is just really good work of which you should be tremendously proud.
Here are a few comments I worked up:
Please select a choice
When you submit your work, will you include the SPSS output for the Shapiro-Wilk test?
Great effort
Hi,
I say it all the time and I have to say it again, because your work here is living proof of it: This course has to be all about the journey of learning, more than whether you got everything right.
As I look through your DAA and the worksheet, I see evidence of that learning. You should feel proud of that; I certainly do.
Here are my specific comments:
Please select a choice 0 1
Good effort
Hi,
I say it all the time and I have to say it again, because your work here is living proof of it: This course has to be all about the journey of learning, more than whether you got everything right.
I could see some of that journey in this, some evidence of effort, and I am really grateful for it. The task is to continue to try to take that up a notch, and make these concepts your own.
Here are my specific comments:
35
420
There is a difference in GPA based on school location.
When you submit your work, will you include the SPSS output for the Levene’s test?
Thanks for all the hard work!
-Dr. Reynolds
Unknown
Please select a choice 0 1
There is a correlation between male and female students.
When you submit your work, will you include the SPSS output for the results of the t-test? Please select a choice Please select a choice
Please select a choice 0 1 Yes
It cannot evaluate the means between more than 2 groups.
No
It doesn’t require assumptions to be satisfied before we can use it.
Not Applicable
It can evaluate whether there’s a statistically significant difference between 2 groups.
It can predict the required sample size for a follow-up study.
Select from drop-down menu boxes
Does the previous GPA correlate with the number of correct final exam scores?
Variable What kind of Variable Is This? What is the Scale of the Variable?
Does gender correlate with previous GPA?
It can evaluate the means between more than 2 groups.
GENDER = Please select a choice Please select a choice 0 0 2 In section 1, you were asked to describe specific elements of the data set by describing the variables themselves. This is pretty important because if we don’t understand the variables and the sort of relationship we’d like to test, then none of this can help us answer any research questions.
I bring all this up because I noticed you had difficulty determining which variable was the predictor and / or which was the outcome. For this data set, the independent variable (or predictor) should have been GENDER and the dependent variable (or outcome) should have been GPA. I would check over your work and figure out where things went wrong.
Along these lines, I should mention you were asked to evaluate which scale of measurement we would use with the GENDER and GPA variables, respectively. I noticed an error or two here. The correct answers (just so you know, so you can compare them to what you did) for GENDER would be nominal (since gender can either be male or female) and for GPA, would be ratio or interval. Why should we care about any of this? Most of the parametric tests you’ll be learning about in this course (such as the t-test) require the dependent variable to be at least ratio. If you try to run those analyses on incompatible variables, your analysis will go kablooey (that’s a technical statistical term, you understand) fairly quickly. In section 1, you were asked to describe specific elements of the data set by describing the variables themselves. This is pretty important because if we don’t understand the variables and the sort of relationship we’d like to test, then none of this can help us answer any research questions.
I bring all this up because I noticed you had difficulty determining which variable was the predictor and / or which was the outcome. For this data set, the independent variable (or predictor) should have been GENDER and the dependent variable (or outcome) should have been GPA. I would check over your work and figure out where things went wrong.
Along these lines, I should mention you were asked to evaluate which scale of measurement we would use with the GENDER and GPA variables, respectively. I noticed an error or two here. The correct answers (just so you know, so you can compare them to what you did) for GENDER would be nominal (since gender can either be male or female) and for GPA, would be ratio or interval. Why should we care about any of this? Most of the parametric tests you’ll be learning about in this course (such as the t-test) require the dependent variable to be at least ratio. If you try to run those analyses on incompatible variables, your analysis will go kablooey (that’s a technical statistical term, you understand) fairly quickly.
The only other thing
I noticed in this section was that your measurement of sample size for the data set appears to be incorrect. It should be 105, reflecting the total number of participants in the study.
In section 1, you were asked to describe specific elements of the data set by describing the variables themselves. This is pretty important because if we don’t understand the variables and the sort of relationship we’d like to test, then none of this can help us answer any research questions.
I bring all this up because I noticed you had difficulty determining which variable was the predictor and / or which was the outcome. For this data set, the independent variable (or predictor) should have been GENDER and the dependent variable (or outcome) should have been GPA. I would check over your work and figure out where things went wrong.
Along these lines, I should mention you were asked to evaluate which scale of measurement we would use with the GENDER and GPA variables, respectively. I noticed an error or two here. The correct answers (just so you know, so you can compare them to what you did) for GENDER would be nominal (since gender can either be male or female) and for GPA, would be ratio or interval. Why should we care about any of this? Most of the parametric tests you’ll be learning about in this course (such as the t-test) require the dependent variable to be at least ratio. If you try to run those analyses on incompatible variables, your analysis will go kablooey (that’s a technical statistical term, you understand) fairly quickly.
The only other thing I noticed in this section was that your measurement of sample size for the data set appears to be incorrect. It should be 105, reflecting the total number of participants in the study.
Do the final exam scores correlate with the geographical areas?
GPA = Please select a choice Please select a choice 0 0 2
The only thing
Does socioeconomic status correlate with the final exam scores?
Please select a choice
nullhyp
What is the overall sample size? Please select a choice 0 2
Previous GPA does not correlate with the number of correct final exam scores.
Gender does not correlate with the previous GPA.
The previous GPA correlates with the number of correct final exam scores.
Gender correlates with the previous GPA.
Please select a choice
althyp
0 0 The previous GPA correlates with the number of correct final exam scores.
Assumptions
Select ‘Yes’ for each assumption that needs to be satisfied when conducting a t-test
opener
good first col, >1 mistake second col
good first col, 1 mistake second
bad first col, good second
bad first col, bad second col
Independence of observations Please select a choice Please select a choice 0 0 Yes Yes 3 Okay, so let’s tackle section 3 of the rubric, the one asking you to evaluate the assumptions that need to be satisfied before doing a t-test. This is the sort of stuff that you either know (based on your reading of the course material) or you don’t. Of course, the real challenge is that once you know it, you’ve got to be able to understand it.
It looks as if you knew it at the definitional level because you identified the assumptions correctly. However, you may have had a bit of trouble applying these definitions because when I look at the DAA and / or your worksheet, I see a few cases where you did not correctly state whether the assumptions applied. Just so you know what all of the correct answers were, let me list them out. The assumptions that have to be met when conducting a t-test are: Independence of observations; Outcome (or dependent) variable is quantitative and normally distributed; and Homogeneity of variance. Of these, only the first and third were met in this data set.
It looks as if you knew it at the definitional level because you identified the assumptions correctly. However, you may have had a bit of trouble applying these definitions because when I look at the DAA and / or your worksheet, I saw one case where you did not correctly state whether the assumption applied. Just so you know what all of the correct answers were, let me list them out. The assumptions that have to be met when conducting a t-test are: Independence of observations; Outcome (or dependent) variable is quantitative and normally distributed; and Homogeneity of variance. Of these, only the first and third were met in this data set.
It looks as if you may not have represented your knowledge correctly (or just didn’t completely nail down that particular piece of knowledge) because I see at least one error in the part where you had to identify assumptions that would need to be satisfied. The three main assumptions actually are: (1) independence of observations; (2) normal distribution of a quantitative dependent variable; and (3) homogeneity of variance.
You did show me you could apply them: When I look at your DAA and your worksheet, I see that you did a great job of highlighting which assumptions were satisfied and which ones weren’t, in the data set.
Okay, so let’s tackle section 3 of the rubric, the one asking you to evaluate the assumptions that need to be satisfied before doing a t-test. This is the sort of stuff that you either know (based on your reading of the course material) or you don’t. Of course, the real challenge is that once you know it, you’ve got to be able to understand it.
The previous GPA does not correlate with the number of correct final exam scores.
Outcome (or dependent) variable is quantitative and normally distributed Please select a choice Please select a choice 0 0 Yes No 3
Homogeneity of variance Please select a choice Please select a choice 0 0 Yes Yes 3 Please select a choice
Variables are linearly related Please select a choice Please select a choice 0 0 No No 3
0.50
0.00
0.05
Gender/GPA
To evaluate these assumptions, please fill in the blanks with the results of the following tests:
Gender/Final
0.90
1 0
Gender/Total
Shapiro-Wilk Test, Statistic = 0 0 Statistic p-value As for the Shapiro-Wilk test, you could very well be on the right track in your understanding of it, though, to be candid, I couldn’t be sure from what I saw in your assignment submissions (I saw at least one error of note skulking about in your work). Let’s take a step back. What does this test do? This test helps us determine whether the data set satisfied the assumption of normal distribution. In this case, since p<.05, the assumption of normal distribution was violated. Remember that for this sort of a test where we’re trying to establish whether assumptions have been met, we want to see statistical NON-significance. Conveniently, SPSS provides the output of the Shapiro-Wilk test for your review. I would revisit the material to see if you can get a better handle on the underlying concepts of this test.
Another important point: The Levene test is something you’ll want to get fairly comfortable with, since you will see it over and over in discussions of the assumptions of parametric tests. Again, I saw an error or two in your treatment of it in your assignment submissions so this is something you’ll want to review. Just so you know, Levene’s test helps us determine if the homogeneity of variance assumption has been met. SPSS can perform the Levene test and produces the output along with the results. Note that just as we saw with the Shapiro-Wilk test, we want Levene’s test to be non-significant (as judged by the p-level).
As for the Shapiro-Wilk test, you could very well be on the right track in your understanding of it, though, to be candid, I couldn’t be sure from what I saw in your assignment submissions (I saw at least one error of note skulking about in your work). Let’s take a step back. What does this test do? This test helps us determine whether the data set satisfied the assumption of normal distribution. In this case, since p<.05, the assumption of normal distribution was violated. Remember that for this sort of a test where we’re trying to establish whether assumptions have been met, we want to see statistical NON-significance. Conveniently, SPSS provides the output of the Shapiro-Wilk test for your review. I would revisit the material to see if you can get a better handle on the underlying concepts of this test.
Another important point: The Levene test is something you’ll want to get fairly comfortable with, since you will see it over and over in discussions of the assumptions of parametric tests. Again, I saw an error or two in your treatment of it in your assignment submissions so this is something you’ll want to review. Just so you know, Levene’s test helps us determine if the homogeneity of variance assumption has been met. SPSS can perform the Levene test and produces the output along with the results. Note that just as we saw with the Shapiro-Wilk test, we want Levene’s test to be non-significant (as judged by the p-level).
As for the Shapiro-Wilk test, you could very well be on the right track in your understanding of it, though, to be candid, I couldn’t be sure from what I saw in your assignment submissions (I saw at least one error of note skulking about in your work). Let’s take a step back. What does this test do? This test helps us determine whether the data set satisfied the assumption of normal distribution. In this case, since p<.05, the assumption of normal distribution was violated. Remember that for this sort of a test where we’re trying to establish whether assumptions have been met, we want to see statistical NON-significance. Conveniently, SPSS provides the output of the Shapiro-Wilk test for your review. I would revisit the material to see if you can get a better handle on the underlying concepts of this test.
Another important point: The Levene test is something you’ll want to get fairly comfortable with, since you will see it over and over in discussions of the assumptions of parametric tests. Again, I saw an error or two in your treatment of it in your assignment submissions so this is something you’ll want to review. Just so you know, Levene’s test helps us determine if the homogeneity of variance assumption has been met. SPSS can perform the Levene test and produces the output along with the results. Note that just as we saw with the Shapiro-Wilk test, we want Levene’s test to be non-significant (as judged by the p-level).
GPA/Final
Shapiro-Wilk Test, p-value =
0.961
0.004
GPA/Total
Final/Total
Levene’s Test, Statistic (F-value) = 0 0 Statistic (F-value) p-value
Levene’s Test, p-value = 0 0
0.095
0.758
Gender/GPA
Gender/Final
GPA/Final
GPA/Total
opener research q Final/Total
Articulate a research question relevant to the statistical test
Every good study begins with a good research question, which is why it’s so important to be able to get this right. Regrettably, your assignment showed that something went wrong here. So, let’s look at this: The research question is what the researcher would like to investigate. It is literally a question, and has to be asked with some precision of language. What does this mean? This means that the research question isn’t something we ask casually: the words have specific meanings. In this case, we were interested in whether male and female students had the same GPA, on average. The answer, therefore, has to be in the research question. Here’s what the question should look like: Does gender have an effect on GPA?
A few more notes: We didn’t have any interest in either the location of the school or students’ age. Similarly, this was a research question suitable for a t-test, not a correlation, so any question about correlation was automatically incorrect.
The null hypothesis you specified, also doesn’t appear to be quite right. Again, null hypotheses have to be right; they’re just not the sort of thing you can get sort of right. Here’s why: The null hypothesis is the opposite of what we think will happen in the study. It is a statement that we reject if p is less than the specified alpha level (typically, .05). When it comes to this assignment, we wondered whether there’s a statistically significant effect, so the null hypotheses had to be the opposite of that statement (no difference in GPA between men and women). If articulation of the null hypothesis is still unclear, I would suggest revisiting the course materials. Understanding what the null hypotheses are and how to formulate them will serve you well not only in this course, but throughout your career.
Now, turning to the alternative hypothesis, something appears to be not entirely right here. The alternative hypothesis is what we’d like to demonstrate in the study. Typically, it’s the affirmative statement of the research question. In our case here, it’s the statement that says that there is a difference between the GPA of male and female students. As with the null hypothesis, it’s super-important to be precise in the way we articulate it. Please reread the textbook (and/or other sources) to make sure you know what an alternative hypothesis is and how to postulate one.
One more thing to know for this section: The alpha level is typically set to .05. Yours wasn’t. In the fourth segment of the rubric, you had to come up with a research question, hypotheses and alpha level.
Every good study begins with a good research question, which is why it’s so important to be able to get this right. Regrettably, your assignment showed that something went wrong here. So, let’s look at this: The research question is what the researcher would like to investigate. It is literally a question, and has to be asked with some precision of language. What does this mean? This means that the research question isn’t something we ask casually: the words have specific meanings. In this case, we were interested in whether male and female students had the same GPA, on average. The answer, therefore, has to be in the research question. Here’s what the question should look like: Does gender have an effect on GPA?
A few more notes: We didn’t have any interest in either the location of the school or students’ age. Similarly, this was a research question suitable for a t-test, not a correlation, so any question about correlation was automatically incorrect.
The null hypothesis you specified, also doesn’t appear to be quite right. Again, null hypotheses have to be right; they’re just not the sort of thing you can get sort of right. Here’s why: The null hypothesis is the opposite of what we think will happen in the study. It is a statement that we reject if p is less than the specified alpha level (typically, .05). When it comes to this assignment, we wondered whether there’s a statistically significant effect, so the null hypotheses had to be the opposite of that statement (no difference in GPA between men and women). If articulation of the null hypothesis is still unclear, I would suggest revisiting the course materials. Understanding what the null hypotheses are and how to formulate them will serve you well not only in this course, but throughout your career.
Now, turning to the alternative hypothesis, something appears to be not entirely right here. The alternative hypothesis is what we’d like to demonstrate in the study. Typically, it’s the affirmative statement of the research question. In our case here, it’s the statement that says that there is a difference between the GPA of male and female students. As with the null hypothesis, it’s super-important to be precise in the way we articulate it. Please reread the textbook (and/or other sources) to make sure you know what an alternative hypothesis is and how to postulate one.
One more thing to know for this section: The alpha level is typically set to .05. Yours wasn’t. In the fourth segment of the rubric, you had to come up with a research question, hypotheses and alpha level.
Every good study begins with a good research question, which is why it’s so important to be able to get this right. Regrettably, your assignment showed that something went wrong here. So, let’s look at this: The research question is what the researcher would like to investigate. It is literally a question, and has to be asked with some precision of language. What does this mean? This means that the research question isn’t something we ask casually: the words have specific meanings. In this case, we were interested in whether male and female students had the same GPA, on average. The answer, therefore, has to be in the research question. Here’s what the question should look like: Does gender have an effect on GPA?
A few more notes: We didn’t have any interest in either the location of the school or students’ age. Similarly, this was a research question suitable for a t-test, not a correlation, so any question about correlation was automatically incorrect.
The null hypothesis you specified, also doesn’t appear to be quite right. Again, null hypotheses have to be right; they’re just not the sort of thing you can get sort of right. Here’s why: The null hypothesis is the opposite of what we think will happen in the study. It is a statement that we reject if p is less than the specified alpha level (typically, .05). When it comes to this assignment, we wondered whether there’s a statistically significant effect, so the null hypotheses had to be the opposite of that statement (no difference in GPA between men and women). If articulation of the null hypothesis is still unclear, I would suggest revisiting the course materials. Understanding what the null hypotheses are and how to formulate them will serve you well not only in this course, but throughout your career.
Now, turning to the alternative hypothesis, something appears to be not entirely right here. The alternative hypothesis is what we’d like to demonstrate in the study. Typically, it’s the affirmative statement of the research question. In our case here, it’s the statement that says that there is a difference between the GPA of male and female students. As with the null hypothesis, it’s super-important to be precise in the way we articulate it. Please reread the textbook (and/or other sources) to make sure you know what an alternative hypothesis is and how to postulate one.
One more thing to know for this section: The alpha level is typically set to .05. Yours wasn’t. Articulate the null hypothesis Please select a choice 0 There is no difference in GPA between male and female students. 4
Articulate the alternative hypothesis Please select a choice 0 There is a difference in GPA between male and female students. 4
Specify the alpha level Please select a choice 0 0.05 4
t-test: Please fill in the blanks:
opener
t-value problem
df problem
p value problem
effect size prob
null hyp prob
degrees of freedom = 0 0
103
Let’s continue on to t-tests, your understanding of which is evaluated in the 5th segment of the scoring rubric for this unit. Remember that a t-test is all about determining whether the means of 2 groups are different in a statistically significant way (meaning that they’re different but not simply because you sampled in a certain way but because if you kept sampling over and over, you’d see the same kind of effect). To get to a p-value which helps you understand whether you are indeed looking at a statistically significant difference, you’ve got to calculate some other statistics, as well.
So, first off, I noticed an error in your calculation of the t-value, which you were supposed to take directly from SPSS output. Any kind of mistake here is due to maybe one of 2 factors:
(1) An incorrect test was performed. Please double-check the SPSS step-by-step guide.
(2) A rounding error
(3) A misunderstanding of what you were looking at
When I look both at your worksheet and the Word doc, I can see a problem with your calculation of degrees of freedom. This, too, was provided for you in the SPSS output for the independent samples t-test. If there is an error here, it’s likely because you copied the wrong number or maybe there’s some sort of rounding error. Remember that since Levene’s test was found not to be significant (we fail to reject the null hypothesis which said that equal variances are assumed), we can use the “equal variance assumed” row (I provided a hint in a red box, right on the worksheet to help you with this).
Effect Size: The effect size you listed is not correct. As discussed within this unit, SPSS doesn’t calculate the effect size for you. You have to compute it manually using a formula that you’ll find in your course materials. I also placed a hint about this in the worksheet. How big of a hint? Well, I did provide the formula. As for interpreting the magnitude of the effect size, Warner (2013) includes a table (5.2) that should help. The announcement I’d posted recently should have helped you with this, as well; I would review it.
Importantly, contrary to what you wrote in your assignment, the null hypothesis should be rejected in this case because it is less than 0.05, our present alpha level). Why is this the case? Please take a look at the textbook as well as other course and non-course materials to get a better understanding of hypothesis testing.
So, first off, I noticed an error in your calculation of the t-value, which you were supposed to take directly from SPSS output. Any kind of mistake here is due to maybe one of 2 factors:
(1) An incorrect test was performed. Please double-check the SPSS step-by-step guide.
(2) A rounding error
(3) A misunderstanding of what you were looking at
When I look both at your worksheet and the Word doc, I can see a problem with your calculation of degrees of freedom. This, too, was provided for you in the SPSS output for the independent samples t-test. If there is an error here, it’s likely because you copied the wrong number or maybe there’s some sort of rounding error. Remember that since Levene’s test was found not to be significant (we fail to reject the null hypothesis which said that equal variances are assumed), we can use the “equal variance assumed” row (I provided a hint in a red box, right on the worksheet to help you with this).
Effect Size: The effect size you listed is not correct. As discussed within this unit, SPSS doesn’t calculate the effect size for you. You have to compute it manually using a formula that you’ll find in your course materials. I also placed a hint about this in the worksheet. How big of a hint? Well, I did provide the formula. As for interpreting the magnitude of the effect size, Warner (2013) includes a table (5.2) that should help. The announcement I’d posted recently should have helped you with this, as well; I would review it.
Importantly, contrary to what you wrote in your assignment, the null hypothesis should be rejected in this case because it is less than 0.05, our present alpha level). Why is this the case? Please take a look at the textbook as well as other course and non-course materials to get a better understanding of hypothesis testing.
As I glance down your paper, I see some problems in what should be simple transcription of descriptive statistics from SPSS output. It looks as if the following aren’t right: mean for females; standard deviation for females; mean for males; standard deviation for males. So, either you made a mistake when you copied the numbers (or filled out the worksheet; note that if the numbers appear as correct in at least one of those formats, you received partial credit), OR you may not have followed carefully enough the step-by-step SPSS guide.
As for the mean difference, the correct answer should have been 0.28 (rounded), which should have been a relatively manageable sort of calculation.
Let’s continue on to t-tests, your understanding of which is evaluated in the 5th segment of the scoring rubric for this unit. Remember that a t-test is all about determining whether the means of 2 groups are different in a statistically significant way (meaning that they’re different but not simply because you sampled in a certain way but because if you kept sampling over and over, you’d see the same kind of effect). To get to a p-value which helps you understand whether you are indeed looking at a statistically significant difference, you’ve got to calculate some other statistics, as well.
So, first off, I noticed an error in your calculation of the t-value, which you were supposed to take directly from SPSS output. Any kind of mistake here is due to maybe one of 2 factors:
(1) An incorrect test was performed. Please double-check the SPSS step-by-step guide.
(2) A rounding error
(3) A misunderstanding of what you were looking at
When I look both at your worksheet and the Word doc, I can see a problem with your calculation of degrees of freedom. This, too, was provided for you in the SPSS output for the independent samples t-test. If there is an error here, it’s likely because you copied the wrong number or maybe there’s some sort of rounding error. Remember that since Levene’s test was found not to be significant (we fail to reject the null hypothesis which said that equal variances are assumed), we can use the “equal variance assumed” row (I provided a hint in a red box, right on the worksheet to help you with this).
Effect Size: The effect size you listed is not correct. As discussed within this unit, SPSS doesn’t calculate the effect size for you. You have to compute it manually using a formula that you’ll find in your course materials. I also placed a hint about this in the worksheet. How big of a hint? Well, I did provide the formula. As for interpreting the magnitude of the effect size, Warner (2013) includes a table (5.2) that should help. The announcement I’d posted recently should have helped you with this, as well; I would review it.
Importantly, contrary to what you wrote in your assignment, the null hypothesis should be rejected in this case because it is less than 0.05, our present alpha level). Why is this the case? Please take a look at the textbook as well as other course and non-course materials to get a better understanding of hypothesis testing.
As I glance down your paper, I see some problems in what should be simple transcription of descriptive statistics from SPSS output. It looks as if the following aren’t right: mean for females; standard deviation for females; mean for males; standard deviation for males. So, either you made a mistake when you copied the numbers (or filled out the worksheet; note that if the numbers appear as correct in at least one of those formats, you received partial credit), OR you may not have followed carefully enough the step-by-step SPSS guide.
As for the mean difference, the correct answer should have been 0.28 (rounded), which should have been a relatively manageable sort of calculation.
Onto confidence intervals: We learned a unit or two ago that confidence intervals help us understand the range of numbers within which a given parameter of interest probably lies. In this part of the assignment, you had to specify the lower and upper bounds of that range, and the SPSS output should have come to your rescue and provided you the 95% confidence interval for the difference between the 2 means. Since we are assuming equal variance here (because Levene’s test was non-significant), the lower and upper bound numbers should have been offered in the first row of the results. Something went wrong here so I would revisit the material, and maybe re-run this in SPSS to see whether you get different results. t-value = 0 0
1.999
p-value = 0 0
0.048
effect size (eta squared) =
0.03734728
descriptive stats problem
CI problem
For the next question, please select from the drop-down box.
As for the mean difference, the correct answer should have been 0.28 (rounded), which should have been a relatively manageable sort of calculation.
Onto confidence intervals: We learned a unit or two ago that confidence intervals help us understand the range of numbers within which a given parameter of interest probably lies. In this part of the assignment, you had to specify the lower and upper bounds of that range, and the SPSS output should have come to your rescue and provided you the 95% confidence interval for the difference between the 2 means. Since we are assuming equal variance here (because Levene’s test was non-significant), the lower and upper bound numbers should have been offered in the first row of the results. Something went wrong here so I would revisit the material, and maybe re-run this in SPSS to see whether you get different results.
mean for females; standard deviation for females; mean for males; standard deviation for males.
Based on the results of the t-test, should the hypothesis be rejected?
As I glance down your paper, I see some problems in what should be simple transcription of descriptive statistics from SPSS output. It looks as if the following aren’t right: mean for females; standard deviation for females; mean for males; standard deviation for males. So, either you made a mistake when you copied the numbers (or filled out the worksheet; note that if the numbers appear as correct in at least one of those formats, you received partial credit), OR you may not have followed carefully enough the step-by-step SPSS guide.
Descriptive statistics for FEMALES
Descriptive statistics for MALES
Mean = 0 0 0 0
2.9719
2.691
Standard Deviation = 0 0 0 0
0.67822
0.73942
standard deviation for males;
Mean difference between the means for males and females = 0 0
0.2809
Please enter the minimum and maximum of the 95% confidence interval for the difference between means for males and females
lower =
0.00215
0.55965
upper =
Please select a choice 0 It can evaluate whether there’s a statistically significant difference between 2 groups. 6
The last section where you had to evaluate the strength and limitation of a t-test is another of those you-either-know-it,-or-you-don’t kinds of situations.
One of your answers here is incorrect, so I would check out the material and see where things didn’t go the way they should have.
The last section where you had to evaluate the strength and limitation of a t-test is another of those you-either-know-it,-or-you-don’t kinds of situations. Both of your answers were incorrect, so I’m not sure what happened here. You might just want to check out the course material and get this moving in the right direction again.
Please select a choice 0 It cannot evaluate the means between more than 2 groups. 6
Please select a choice
strongcorr
Strong positive
Strong negative
Weak negative
Weak positive
Please select a choice
evallp
It can evaluate whether there is a relationship between 2 variables.
It can evaluate whether one of the variables causes another variable.
It can evaluate whether the sample size needs to be larger.
It can evaluate whether there is a relationship between homoscedacity and homogeneity.
Please select a choice
astudio
It cannot evaluate whether there is a relationship between 2 variables.
It cannot evaluate whether one of the variables causes another variable.
It can evaluate whether there is a relationship between homoscedacity and homogeneity.
0
1
ENTER NAME HERE—>
Variable
What kind of Variable Is This?
What is the Scale of the Variable?
Presence of Music (Whether Music Was Played) =
Please select a choice
Reading Comprehension Scores =
What is the overall sample size?
Assumptions
Select ‘
Yes
Independence of observations
Outcome (or dependent) variable is quantitative and normally distributed
Homogeneity of variance
Variables are linearly related
The numbers look pretty in pink font
Presence of bivariate outliers
Articulate a research question relevant to the main statistical test
Articulate the null hypothesis
Articulate the alternative hypothesis
Specify the alpha level
(The alpha level can be inferred from the article, though it isn’t e
x
Fill in the blanks to report the results from the main One-Way ANOVA you saw in the article.
F value =
p-value =
effect size (eta2) =
Select answers from the drop-down boxes to interpret the main One-Way ANOVA you saw in the article.
Degrees of freedom =
Is the effect size big or small? Use Table
5
3
Based on the results of the ANOVA, should the null hypothesis be rejected?
What is the primary conclusion that can be drawn from the main test in this study?
Please select a choice 1
What was a strength of the study as reported in the article?
What is the main limitation of the study as reported in the article?
Hold on! You’re not done. You still have 22 question(s) to answer.
(and your name is one of them)
This worksheet is absolutely positively required. In fact, it is the ONLY thing you’ll need to submit for this assignment.
No
(1) This worksheet is based on the journal article and instructions I posted in Updates / Handouts. You must answer based on that article and that article alone. Contrary to the original instructions for this assignment, NO OTHER ARTICLE will be accepted for this assignment.
(2) In this assignment, you will ONLY be looking at the main test featured in the article. We are NOT interested in the other tests. The article talks about a breakdown by gender, for example. We are not interested in that for the purposes of this assignment. It also talks about correlations; we aren’t interested in those either. We are interested ONLY in the main test: the ONE-WAY ANOVA. If you’re not sure what I’m talking about, you should be able to figure it out from the article itself. If you still can’t, then please note the variables below. So, please answer all the questions below with the main test alone in mind.4
OUTPUT
33%
ENTER NAME HERE—> 0
GREAT!
VERY GOOD!
NOT GOOD
Okay, as for sample size, this one should have been a piece of cake, as it comes directly from the article. Either you just selected the wrong choice from the drop-down by accident, or something went wrong. I would recheck the article and see where things went a little sideways.
Locate scholarly article
10
0%
20%
Section 1: Data Context
In any study involving a t-test or One-Way ANOVA, we are always testing to see if one variable has an effect on another. That’s the whole reason for doing these types of studies and tests. So, if you wanted to do one of these tests, what’s the first thing you’d do? Figure out which variable you believe will have an effect on the other. Well, that’s what you were (sort of) asked to do in this assignment. In this case, you had to figure out which variable the researchers considered to be the predictor (or independent) variable, and which they considered to be the outcome (or dependent) variable. Think of this as your ‘ticket to ride,’ so to speak: You can’t really evaluate what’s happening in the article if you don’t know which variable is being tested for an effect on which other. I noticed at least one error in your answers so this is something you’re just going to have to buckle down and figure out. Either you selected the incorrect answer(s) in the drop-down or something is missing from your learning. I would figure this out before you hit the final assignment for sure.
Scale of measurement for one of these variables could be tricky, which is why I gave full credit for reasonable answers. That said, there were some unreasonable ones among your choices, so you did have to think this through and figure out which would be reasonable, particularly for the Reading Comprehension variable. The “Presence of Music” variable was fairly straightforward: That had to be nominal. No, it can’t be ordinal. If you have any doubt of this, just check out a number of Web sites that list “yes / no” as a nominal variable (what I’m trying to hint at here is that if you understood that “Presence of Music” has the values of “yes” or “no,” then this was a fairly straightforward scale of measurement to knock out). I also pushed hard in my comments on previous work to make sure you understood the predictor for a t-test as a nominal variable (see? There’s always method to the madness). As for Reading Comprehension, that was the tricky one. I could see arguments for
Ratio
Interval
Provide context
15%
Hi ,
Congratulations on a well-earned victory! You did a marvelous job on this!!!
Let’s think about what this means. You’ve now parsed a real, honest-to-goodness research article into its statistical and conceptual components. Not bad for a few weeks of statistics work, huh?
Here are some more specific comments:
Hi ,
Good, solid effort!
Let’s think about what this means. You’ve now begun moving down a path toward parsing a real, honest-to-goodness research article into its statistical and conceptual components. Not bad for a few weeks of statistics work, huh?
Here are some more specific comments:
Hi ,
I’m grateful you gave this a shot. With some more focus, this might have come together.
Let me be candid: This should have come together. There’s no reason it should not have come together. The first and last components of the rubric were given to you by virtue of the worksheet. The rest of it depended largely on making an effort to read the article – not even reading it well or thinking about it – just reading it. So, if things didn’t quite work out, then this may be the right time to step back and ask yourself why you didn’t ace this.
Why am I saying this? I really don’t want you walking away from this assignment thinking that what happened here had anything to do with your ability to do statistics. I don’t know what happened here, but the one thing of which I’m absolutely confident, is that your ability to do statistics didn’t get a fighting chance at bat. What I’m trying to say is that if this had been about your ability to do statistics, then you would have done a whole lot better. Yes, I know that about you at this point.
Here are some more specific comments:
Presence of Music (Whether Music Was Played) = Please select a choice Please select a choice
Predictor (or Independent) variable
Nominal
In any study involving a t-test or One-Way ANOVA, we are always testing to see if one variable has an effect on another. That’s the whole reason for doing these types of studies and tests. So, if you wanted to do one of these tests, what’s the first thing you’d do? Figure out which variable you believe will have an effect on the other. Well, that’s what you were (sort of) asked to do in this assignment. In this case, you had to figure out which variable the researchers considered to be the predictor (or independent) variable, and which they considered to be the outcome (or dependent) variable. Think of this as your ‘ticket to ride,’ so to speak: You can’t really evaluate what’s happening in the article if you don’t know which variable is being tested for an effect on which other. I noticed at least one error in your answers so this is something you’re just going to have to buckle down and figure out. Either you selected the incorrect answer(s) in the drop-down or something is missing from your learning. I would figure this out before you hit the final assignment for sure.
3 Assumptions 0%
10%
Congratulations on a well-earned victory! You did a marvelous job on this!!!
Let’s think about what this means. You’ve now parsed a real, honest-to-goodness research article into its statistical and conceptual components. Not bad for a few weeks of statistics work, huh?
Here are some more specific comments:
Yes
Reading Comprehension Scores = Please select a choice Please select a choice
Outcome (or Dependent) Variable
Ordinal
Okay, as for sample size, this one should have been a piece of cake, as it comes directly from the article. Either you just selected the wrong choice from the drop-down by accident, or something went wrong. I would recheck the article and see where things went a little sideways.
4 Research Questions, Null Hypothesis, Alpha Level
Onward and upward — one assignment to go — this one, as you know, is due June 1
7
Looking forward to your strong finish!
-Dr. Reynolds
5
Results and Interpretation
17%
What is the overall sample size? Please select a choice
334
6
Conclusion
CLEAN SWEEP, !
Congratulations on a well-earned victory.
Let’s think about what this means. You’ve now parsed a real, honest-to-goodness research article into its statistical and conceptual components. Not bad for a few weeks of statistics work, huh?
Some parts of this assignment may have been a breeze, and they probably were. But some required some critical thinking around the concepts for the unit. You executed those beautifully. Again, congratulations!
Onward and upward — one assignment to go — this one, as you know, is due June 17 at 5 pm CST. Both a worksheet AND a Word doc (DAA) are required for this one. I’ve posted the worksheet in Updates / Handouts, so you’re free to get started on it.
Looking forward to your strong finish!
-Dr. Reynolds
7
Writing
100%
Moderator variable
Section 2: Testing Assumptions
Now, let’s talk about assumptions. I won’t lie: Assumptions are a bit of a pain in the neck. I’d love to be able to do these tests without having to worry about whether certain assumptions are satisfied. But there’s no getting around them. From a learning perspective, assumptions are important because if we understand the concepts behind the tests, then we should know why those assumptions matter. As for the article, it didn’t contain any notations on how the researchers dealt with assumptions. Fortunately, that shouldn’t be a problem for us because we know the researchers did an ANOVA and we learned about the assumptions for those. It turns out that ANOVAs require independence of observations, the outcome (or dependent) variable must be quantitative and normally distributed, and there must be homogeneity of variance. Of course, you’ll recognize these from t-tests, which makes sense because ANOVA is really just a way of doing t-testing without compounding the risk of Type I error. The rest of the assumptions are not required for a One-Way ANOVA. It goes without saying, obviously, that the numbers should never look pretty in pink font: that’s a big no-no in scholarly writing. From what I can tell, you made at least one error in this section. You’ll want to compare your worksheet with the answers I just put in this feedback, figure out where you went wrong, and then make sure you’re locked and loaded for the next assignment which turns out to be about what? You guessed it: ANOVA!
Mediator variable
COMMENTS
Assumptions
Select ‘Yes’ for each assumption that needs to be satisfied when conducting the main test (the ONE-WAY ANOVA) featured in the article
Hi ,
Congratulations on a well-earned victory! You did a marvelous job on this!!!
Let’s think about what this means. You’ve now parsed a real, honest-to-goodness research article into its statistical and conceptual components. Not bad for a few weeks of statistics work, huh?
Here are some more specific comments:
In any study involving a t-test or One-Way ANOVA, we are always testing to see if one variable has an effect on another. That’s the whole reason for doing these types of studies and tests. So, if you wanted to do one of these tests, what’s the first thing you’d do? Figure out which variable you believe will have an effect on the other. Well, that’s what you were (sort of) asked to do in this assignment. In this case, you had to figure out which variable the researchers considered to be the predictor (or independent) variable, and which they considered to be the outcome (or dependent) variable. Think of this as your ‘ticket to ride,’ so to speak: You can’t really evaluate what’s happening in the article if you don’t know which variable is being tested for an effect on which other. I noticed at least one error in your answers so this is something you’re just going to have to buckle down and figure out. Either you selected the incorrect answer(s) in the drop-down or something is missing from your learning. I would figure this out before you hit the final assignment for sure.
Okay, as for sample size, this one should have been a piece of cake, as it comes directly from the article. Either you just selected the wrong choice from the drop-down by accident, or something went wrong. I would recheck the article and see where things went a little sideways.
Now, let’s talk about assumptions. I won’t lie: Assumptions are a bit of a pain in the neck. I’d love to be able to do these tests without having to worry about whether certain assumptions are satisfied. But there’s no getting around them. From a learning perspective, assumptions are important because if we understand the concepts behind the tests, then we should know why those assumptions matter. As for the article, it didn’t contain any notations on how the researchers dealt with assumptions. Fortunately, that shouldn’t be a problem for us because we know the researchers did an ANOVA and we learned about the assumptions for those. It turns out that ANOVAs require independence of observations, the outcome (or dependent) variable must be quantitative and normally distributed, and there must be homogeneity of variance. Of course, you’ll recognize these from t-tests, which makes sense because ANOVA is really just a way of doing t-testing without compounding the risk of Type I error. The rest of the assumptions are not required for a One-Way ANOVA. It goes without saying, obviously, that the numbers should never look pretty in pink font: that’s a big no-no in scholarly writing. From what I can tell, you made at least one error in this section. You’ll want to compare your worksheet with the answers I just put in this feedback, figure out where you went wrong, and then make sure you’re locked and loaded for the next assignment which turns out to be about what? You guessed it: ANOVA!
At this point in the course, you should have a pretty solid sense of how to state a research question, null hypothesis, alternative hypothesis, and alpha level. Having read the article, you should also have a good handle on how each of those plays out in this specific case. As the worksheet emphasized repeatedly, you are asked to analyze the primary effect in this study which is whether there’s an effect of lyrical music on reading comprehension scores for junior high school students. The null hypothesis is that there’s no effect. The alternative is that there is. As for alpha level (and as the worksheet pointed out), none was specified in the article but you could either have figured it out from the way the article talked about the threshold of significance, OR you could have just listed the alpha level that’s most customarily used. That alpha level is, of course, .05. At least one of these elements was incorrect in your worksheet so you’ll want to dive back into the material to make sense you’ve got this locked down.
Onto the next section . . . F value (
193.6
(1,332)
The last part required a touch of critical thinking but more just good ol’ fashioned reading skills than anything else. The strength and limitation were pulled directly from the article. The strength answer should have been “
All of the above.
The researchers didn’t test for reading and attentional ability.
Looking forward to your strong finish!
-Dr. Reynolds
Independence of observations Please select a choice Yes 0
Now, let’s talk about assumptions. I won’t lie: Assumptions are a bit of a pain in the neck. I’d love to be able to do these tests without having to worry about whether certain assumptions are satisfied. But there’s no getting around them. From a learning perspective, assumptions are important because if we understand the concepts behind the tests, then we should know why those assumptions matter. As for the article, it didn’t contain any notations on how the researchers dealt with assumptions. Fortunately, that shouldn’t be a problem for us because we know the researchers did an ANOVA and we learned about the assumptions for those. It turns out that ANOVAs require independence of observations, the outcome (or dependent) variable must be quantitative and normally distributed, and there must be homogeneity of variance. Of course, you’ll recognize these from t-tests, which makes sense because ANOVA is really just a way of doing t-testing without compounding the risk of Type I error. The rest of the assumptions are not required for a One-Way ANOVA. It goes without saying, obviously, that the numbers should never look pretty in pink font: that’s a big no-no in scholarly writing. From what I can tell, you made at least one error in this section. You’ll want to compare your worksheet with the answers I just put in this feedback, figure out where you went wrong, and then make sure you’re locked and loaded for the next assignment which turns out to be about what? You guessed it: ANOVA!
Supercilious
Is there an effect of reading comprehension on lyrical music response in jr. high school students?
Outcome (or dependent) variable is quantitative and normally distributed Please select a choice Yes 0
Is there an effect of lyrical music on gender identification for adolescents?
Homogeneity of variance Please select a choice Yes 0
Is there an effect of lyrical music on reading comprehension for jr. high school students?
Variables are linearly related Please select a choice No 0
Is there an effect of reading comprehension on math skills in jr. high school students?
The numbers look pretty in pink font Please select a choice No 0
Presence of bivariate outliers Please select a choice No 0 Please select a choice
There is an effect of reading comprehension on math skills in jr. high school students.
There is no effect of lyrical music on reading comprehension for jr. high school students.
Section 3: Research Question, Hypotheses, Alpha Level
There is an effect of lyrical music on reading comprehension for jr. high school students.
At this point in the course, you should have a pretty solid sense of how to state a research question, null hypothesis, alternative hypothesis, and alpha level. Having read the article, you should also have a good handle on how each of those plays out in this specific case. As the worksheet emphasized repeatedly, you are asked to analyze the primary effect in this study which is whether there’s an effect of lyrical music on reading comprehension scores for junior high school students. The null hypothesis is that there’s no effect. The alternative is that there is. As for alpha level (and as the worksheet pointed out), none was specified in the article but you could either have figured it out from the way the article talked about the threshold of significance, OR you could have just listed the alpha level that’s most customarily used. That alpha level is, of course, .05. At least one of these elements was incorrect in your worksheet so you’ll want to dive back into the material to make sense you’ve got this locked down.
There is no correlation between male and female students.
Articulate a research question relevant to the main statistical test Please select a choice Is there an effect of lyrical music on reading comprehension for jr. high school students? 0
At this point in the course, you should have a pretty solid sense of how to state a research question, null hypothesis, alternative hypothesis, and alpha level. Having read the article, you should also have a good handle on how each of those plays out in this specific case. As the worksheet emphasized repeatedly, you are asked to analyze the primary effect in this study which is whether there’s an effect of lyrical music on reading comprehension scores for junior high school students. The null hypothesis is that there’s no effect. The alternative is that there is. As for alpha level (and as the worksheet pointed out), none was specified in the article but you could either have figured it out from the way the article talked about the threshold of significance, OR you could have just listed the alpha level that’s most customarily used. That alpha level is, of course, .05. At least one of these elements was incorrect in your worksheet so you’ll want to dive back into the material to make sense you’ve got this locked down.
Please select a choice
Articulate the null hypothesis Please select a choice There is no effect of lyrical music on reading comprehension for jr. high school students. 0
72 (but with no striation)
Articulate the alternative hypothesis Please select a choice There is an effect of lyrical music on reading comprehension for jr. high school students. 0 334 There is an effect of lyrical music on reading comprehension for jr. high school students.
Specify the alpha level Please select a choice
0.05
420
There is a difference in GPA based on school location.
Unknown
Section 4: Results and Interpretation
Onto the next section . . . F value (193.6), p-value (.001), and Degrees of freedom (1,332) were plainly spelled out in the article. How plainly were they spelled out? Pretty much as I spelled them out in the worksheet. As for effect size (0.61), I pointed you to the table. All you had to do was pull the right effect size from the article, compare it to that table, and then look through the answer choices in the worksheet. The answer was literally in the question. Finally, as for the question about whether the null should have been rejected (answer = yes), that should have been feasible to figure out IF you understand how null hypothesis testing works, if you’d studied the article and understood it, and if you’d worked to understand the principles of one-way ANOVA. Those are a lot of IFs so if they didn’t all come together, please jump on them now before you hit the next assignment. My review of your worksheet shows at least one thing went wrong in this section, so I would do some review.
Please select a choice Please select a choice
Onto the next section . . . F value (193.6), p-value (.001), and Degrees of freedom (1,332) were plainly spelled out in the article. How plainly were they spelled out? Pretty much as I spelled them out in the worksheet. As for effect size (0.61), I pointed you to the table. All you had to do was pull the right effect size from the article, compare it to that table, and then look through the answer choices in the worksheet. The answer was literally in the question. Finally, as for the question about whether the null should have been rejected (answer = yes), that should have been feasible to figure out IF you understand how null hypothesis testing works, if you’d studied the article and understood it, and if you’d worked to understand the principles of one-way ANOVA. Those are a lot of IFs so if they didn’t all come together, please jump on them now before you hit the next assignment. My review of your worksheet shows at least one thing went wrong in this section, so I would do some review.
Yes
It cannot evaluate the means between more than 2 groups.
F value = 0 193.6 0 No
It doesn’t require assumptions to be satisfied before we can use it.
p-value = 0
0.00
Not Applicable
It can evaluate whether there’s a statistically significant difference between 2 groups.
effect size (eta2) = 0.00
0.61 or .37
It can predict the required sample size for a follow-up study.
Degrees of freedom = Please select a choice (1,332) 0
Is the effect size big or small? Use Table 5.2 in Warner (2013) to help you.
It’s extremely large, exceeding the highest value of .5 in Table 5.2 of the text.
It’s small. It shows up at the lower end of the table in Warner’s textbook.
Based on the results of the ANOVA, should the null hypothesis be rejected? Please select a choice Yes 0
Does the previous GPA correlate with the number of correct final exam scores?
Does gender correlate with previous GPA?
It can evaluate the means between more than 2 groups.
Do the final exam scores correlate with the geographical areas?
The last part required a touch of critical thinking but more just good ol’ fashioned reading skills than anything else. The strength and limitation were pulled directly from the article. The strength answer should have been “All of the above.” and the limitation should have been, “The researchers didn’t test for reading and attentional ability.” If you’re in doubt, just check the article. The main conclusion could be derived with a little bit of logic grounded in the work you did in the null hypothesis testing section of the assignment, combined with a good reading of the article. I did see at least one incorrect answer in this section, so you might want to backtrack and see where you might have been misled.
Does socioeconomic status correlate with the final exam scores?
Section 5: Conclusion
Please select a choice
nullhyp
What is the primary conclusion that can be drawn from the main test in this study? Please select a choice
Lyrical music has an effect on reading comprehension for adolescents.
The last part required a touch of critical thinking but more just good ol’ fashioned reading skills than anything else. The strength and limitation were pulled directly from the article. The strength answer should have been “All of the above.” and the limitation should have been, “The researchers didn’t test for reading and attentional ability.” If you’re in doubt, just check the article. The main conclusion could be derived with a little bit of logic grounded in the work you did in the null hypothesis testing section of the assignment, combined with a good reading of the article. I did see at least one incorrect answer in this section, so you might want to backtrack and see where you might have been misled.Previous GPA does not correlate with the number of correct final exam scores.
What was a strength of the study as reported in the article? Please select a choice All of the above. 0
Gender does not correlate with the previous GPA.
What is the main limitation of the study as reported in the article? Please select a choice The researchers didn’t test for reading and attentional ability. 0
The previous GPA correlates with the number of correct final exam scores.
Gender correlates with the previous GPA.
Please select a choice
althyp
The previous GPA correlates with the number of correct final exam scores.
The previous GPA does not correlate with the number of correct final exam scores.
Please select a choice
0.50
0.00 Please select a choice
0.05
Gender/GPA
Gender/Final
0.90
Gender/Total
GPA/Final
GPA/Total
Final/Total
Gender/GPA
Gender/Final
GPA/Total
Final/Total (1,332)
(2,333)
(13,32)
18.72 ~ 19.4
Cannot be Determined
Reading comprehension is different for males vs. females.
Lyrical music has an effect on reading comprehension for adolescents.
Daniel Powter’s Bad Day has the strongest effect on reading comprehension.
Point biserial correlations showed no effect of reading comprehension on gender bias.
Results were inconclusive. More work needs to be done.
It added to the literature of a topic for which conflicting findings have emerged.
It made use of a population that isn’t well represented in the literature.
The researchers chose music that would appeal to the participants.
All of the above.
None of the above.
The researchers used a one-way ANOVA but should have used a histogram instead.
The researchers didn’t test for reading and attentional ability.
The researchers did not use SPSS.
Please select a choice
strongcorr
Strong positive
Strong negative
Weak negative
Weak positive
Please select a choice
evallp
It can evaluate whether there is a relationship between 2 variables.
It can evaluate whether one of the variables causes another variable.
It can evaluate whether the sample size needs to be larger.
It can evaluate whether there is a relationship between homoscedacity and homogeneity.
Please select a choice
astudio
It cannot evaluate whether there is a relationship between 2 variables.
It cannot evaluate whether one of the variables causes another variable.
It can evaluate whether there is a relationship between homoscedacity and homogeneity. It’s extremely large, exceeding the highest value of .5 in Table 5.2 of the text.
It’s big but still under the max in Table 5.2 of Warner’s textbook.
It’s small. It shows up at the lower end of the table in Warner’s textbook.
We can’t determine this.