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e C
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mmon
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se va
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ia
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ion.
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. Define assi
g
nable cause variation.
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. In t
h
e
d
a
y
to day operations of the process why is it important that we understand if the variation we see in a product/process comes from common or assignable cause situations?
4
. Define a population.
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. Define a sample:
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. Define a random sample:
7. Define a stratified sample and give one example.
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F
or the following set of sample data calculate each of the values below:
Sample data set:
11
, 1
0
, 8, 13,
14
, 12, 11, 11, 13, 11, 11
Mean:
Median:
Mode:
Range:
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W
hat are the two key principles you try to follow when conducting a brainstorming session? (4 points)
10. Create a Pareto Diagram from the following data.
Type of Defect |
Number of Defects |
Overesize Diameter |
20 |
Undersize Diameter |
6 |
Rusty |
14 |
Scratched |
5 |
Excessive Tool Marks |
11 |
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11. What advantage does a Cause & Effect Diagram offer over traditional brainstorming sessions?
12. Determine the area under the normal curve for each of the following conditions. Diagram re
q
uired.
· Area under the curve > Z = 1.34
· Area under the curve between Z = -2.15 and Z = -0.45
· Area under the curve < Z = 1.89
· Area under the curve < Z = -1.65 and > Z = 2.10 (Note: both areas)
13) The output for a normally distributed process results in an average size of 43 Rc with a standard deviation of 2.1 Rc”. If the customer specifications are 40 Rc to 52 Rc, are there defective products being made? Mathematical analysis required for credit.
14. What is a requirement of the data collections process to be able to use a “run” chart? (4 points)
15. If the customer specifications are in pounds and are 13.00 ± 0.15, given the following histogram, are defective parts being made? Justify your answer to receive credit. (4 points)
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