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Question 1

4 out of 4 points    

Understanding variation is important because variation:    

 

 

 

     Question 2

4 out of 4 points    

The Statistical Thinking Strategy illustrated in Figure 2.14 provides a graphic of the overall approach to driving improvement through statistical thinking. Which of the following is a key principle illustrated in this specific graph?    

 

 

 

     Question 3

4 out of 4 points    

Improving the quality of process measurements is:    

 

 

 

     Question 4

4 out of 4 points    

The Hidden Factory is:    

 

 

 

     Question 5

4 out of 4 points    

Which type of variation was critical to resolving the realized revenue case study?    

 

 

 

     Question 6

4 out of 4 points    

A process is said to be capable if:    

 

 

 

     Question 7

4 out of 4 points    

The histogram below showing ages of credit card holders displays what type of distribution?
 
   

 

 

 

     Question 8

4 out of 4 points    

In evaluating data on our process outputs, four characteristics we might investigate are: central tendency, variation, shape of distribution, and stability. Which of the following tools would be most helpful to determine stability of the process?    

 

 

 

     Question 9

4 out of 4 points    

Non-random and unpredictable patterns on a control chart indicate:    

 

 

 

     Question 10

4 out of 4 points    

A main purpose of a control chart is to:    

 

 

 

     Question 11

4 out of 4 points    

Models based on subject matter fundamentals (theory) are generally better than statistical models for:    

 

 

 

     Question 12

4 out of 4 points    

A statistic that is used to indicate too much correlation between the predictors in a regression analysis is called the:    

 

 

 

     Question 13

4 out of 4 points    

George Box tells us “all models are wrong but some are useful”. By this comment he means:    

 

 

 

     Question 14

4 out of 4 points    

Tips for building useful models include:    

 

 

 

     Question 15

4 out of 4 points    

The best way to evaluate the validity of a statistical model is:    

 

 

 

     Question 16

4 out of 4 points    

Given the plot below, what might you suspect about factors A and B?
 
   

 

 

 

     Question 17

4 out of 4 points    

The following table shows data on the effect of Machine Pressure on product hardness.   What statistical test should be used to test the effect of pressure on average hardness?
 

100MPa

200MPa

6.2

11.1

7.3

10.3

8.2

13

8.3

14.3

7.5

11.2

6.5

14.7

9.6

10

9

9.4    

 

 

 

     Question 18

4 out of 4 points    

What should one consider when analyzing the results of an experiment?    

 

 

 

     Question 19

4 out of 4 points    

In every experiment there is experimental error.  Which of the following statements is true?    

 

 

 

     Question 20

4 out of 4 points    

A 32 experiment means that we are experimenting with:    

 

 

 

     Question 21

4 out of 4 points    

We are conducting a poll for the mayoral election of a medium sized city, and found with one week before the election that the Democrat candidate is leading with 52% planning to vote for her, 46% planning to vote for the Republican, with 2% not sure. The 95% confidence interval for proportion planning to vote for the Democrat is +/- 3%. Based on this information, and making reasonable assumptions, which of the following statements is correct?    

 

 

 

     Question 22

4 out of 4 points    

For which of the following scenarios am I most likely to utilize a Chi-squared test?    

 

 

 

     Question 23

4 out of 4 points    

After running an ANOVA comparing the average years of experience between five different job classifications, we obtained a p value of .02. Which of the following would be a reasonable conclusion concerning the population in this case?    

 

 

 

     Question 24

4 out of 4 points    

Which of the following could be considered a prediction interval?    

 

 

 

     Question 25

4 out of 4 points    

What would happen (other things equal) to a confidence interval if you calculated a 99 percent confidence interval rather than a 95 percent confidence interval?    

 

 

 

     

 

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