A
SSIGNM
E
NT #
6
1
. You want to randomly select a number between 1 and
10
, using Microsoft Excel. Which function do you use?
a. |
RANK |
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b. |
RAN D |
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c. |
RAND B ETWEEN |
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d. |
Microsoft Excel does not have these capabilities |
2
. A population consists of
8
items. The number of different simple random samples of size
3
that can be selected from this population is
2 4 |
5 6 |
512 |
128 |
3. Whenever the population has a normal probability distribution, the sampling distribution of is a normal probability distribution for
only large sample sizes |
only small sample sizes |
any sample size |
only samples of size thirty or greater |
4. Which of the following sampling methods does not lead to probability samples?
stratified sampling |
cluster sampling |
systematic sampling |
convenience sampling |
5. The purpose of statistical inference is to provide information about the
sample based upon information contained in the population |
population based upon information contained in the sample |
population based upon information contained in the population |
mean of the sample based upon the mean of the population |
6. As a rule of thumb, the sampling distribution of the sample proportion can be approximated by a normal probability distribution whenever
np 5 |
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n(1 – p) 5 and n 30 |
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n 30 and (1 – p) = 0.5 |
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d. |
none of these alternatives is correct |
Answer questions
7
and 8 based on the following:
A random sample of 10 examination papers in a course, which was given on a pass or fail basis, showed the following scores.
Paper Number |
Grade |
Status |
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1 |
65 |
Pass |
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2 |
87 |
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3 |
9 2 |
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4 |
35 |
Fail |
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5 |
79 |
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6 |
100 |
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7 |
48 |
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8 |
74 |
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9 | |||||||||||
10 |
91 |
7. The point estimate for the mean of the population is
75 0 |
|
85 |
|
75 |
8. The point estimate for the
proportion of all students who passed the course is
0.8 |
0.2 |
1.8 |
1.2 |
9. A sample of 24 observations is taken from a population that has 150 elements. The sampling distribution of is
approximately normal because is always approximately normally distributed |
approximately normal because the sample size is large in comparison to the population size |
approximately normal because of the central limit theorem |
normal if the population is normally distributed |
10. A population has a mean of 75 and a standard deviation of 8. A random sample of
800
is selected. The expected value of is
800 |
11. A sample of 92 observations is taken from an infinite population. The sampling distribution of is approximately
normal because is always approximately normally distributed |
normal because the sample size is small in comparison to the population size |
normal because of the central limit theorem |
Answer questions 12 – 14 based on the following:
C
onsider a population of five families with the following data representing the number of children in each family.
Family |
# Children |
A | |
B | |
C | |
D | |
E |
12. Determine the sampling distribution of for n = 2 (recall our discussion of how to generate a sampling distribution of ). You should record your results in a frequency tabl
e.
How many unique values does your random variable take on?
16 |
13. Refer to Question 12. Compute the expected value of .
3.2 |
14. State whether or not your results in Question 13
support
the following statement: “ is an unbiased estimator of μ”
support |
do not support |
Answer questions 15 – 16 based on the following:
The average score for female golfers is 106. Use this value as the population mean and assume that the population standard deviation is 14 strokes.
15. A simple random sample of 45 female golfers is taken. What is the probability that the sample mean is within 3 strokes of the population mean for the sample of female golfers?
0.758 |
|||
0.166 |
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0.850 |
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0.379 |
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e. |
0.500 |
16. Assume that female golf scores are distributed normally. What is the probability that a randomly selected female golfer’s score is within 3 strokes of the population mean?
a.
0.758
b.
0.166
c.
0.850
d.
0.379
e.
0.500
17. Random samples of size 100 are taken from an infinite population whose population proportion is 0.2. The mean and standard error of the proportion are
0.2 and 0.04 |
0.2 and 0.2 |
20 and 0.04 |
20 and 0.2 |
18. In a local university, 40% of the students live in the dormitories. A random sample of 80 students is selected for a particular study. The probability that the sample proportion (the proportion living in the dormitories) is between 0.30 and 0.50 is
0.4664 |
0.9328 |
0.0336 |
0.0672 |
19. A sample of 51 observations will be taken from an infinite population. The population proportion equals 0.85. The probability that the sample proportion will be between 0.9115 and 0.946 is
a.
0.8633
b.
0.6900
c.
0.0819
d.
0.0345
20. A population has a mean of 53 and a standard deviation of 21. A sample of 49 observations will be taken. The probability that the sample mean will be greater than 57.95 is
a.
0
b.
0.0495
c.
0.4505
d.
0.9505
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