Improve Phase Test
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Question 1 of 61
1. Question
If the correlation coefficient of two variables is zero, the two variables are independent?
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Question 2 of 61
2. Question
Correlation implies causation?
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Question 3 of 61
3. Question
R2 measures the proportion of variability in the data which can be explained by the model?
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Question 4 of 61
4. Question
In a multiple linear regression analysis, the pvalues of the insignificant predictors are the ones that are smaller than the alpha level?
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Question 5 of 61
5. Question
When eliminating insignificant variables from a multiple linear regression model, we should remove all insignificant variables at the same time?
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Question 6 of 61
6. Question
Multicollinearity is the situation when two or more independent variables in a multiple regression model are correlated with each other?
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Question 7 of 61
7. Question
Replication in DOE increases the total degrees of freedom?
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Question 8 of 61
8. Question
Fractional factorial experiments require fewer resources and runs than full factorial experiments?
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Question 9 of 61
9. Question
Which of the following situations does NOT indicate that the simple linear regression model is statistically significant?
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Question 10 of 61
10. Question
What is the total degrees of freedom of a simple linear regression model built using 25 data points?
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Question 11 of 61
11. Question
Which of the following assumptions is NOT required to ensure the reliability of the linear regression model?
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Question 12 of 61
12. Question
In a twolevel full factorial DOE with four factors, how many runs should there be?
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Question 13 of 61
13. Question
In an orthogonal design, the sum of products for each run should equal zero?
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Question 14 of 61
14. Question
What is the resolution of a 231 DOE?
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Question 15 of 61
15. Question
Pearson’s correlation coefficient measures both linear and nonlinear relationship between two variables?
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Question 16 of 61
16. Question
In a resolution III design, the main effects are confounded with?
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Question 17 of 61
17. Question
A correlation coefficient of 0.00 means there is absolutely no relationship?
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Question 18 of 61
18. Question
Which of the following correlation coefficients best represents a strong positive linear relationship?
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Question 19 of 61
19. Question
Which of the following correlation coefficients best represents a strong inverse linear relationship?
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Question 20 of 61
20. Question
Which of the following correlation coefficients best represents a moderate positive linear relationship?
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Question 21 of 61
21. Question
Which of the following correlation coefficients best represents the absence of a linear relationship?
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Question 22 of 61
22. Question
Which of the following correlation coefficients do not represent a perfect linear relationship?
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Question 23 of 61
23. Question
Which of the following is a way in which you might deal with multicollinearity?
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Question 24 of 61
24. Question
Would increasing the sample size be an effective way to deal multicollinearity?
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Question 25 of 61
25. Question
If VIF ≥ 10, there is no multicollinearity?
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Question 26 of 61
26. Question
If VIF = 1, there is no multicollinearity?
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Question 27 of 61
27. Question
Experiments are passive studies in which historical data are used to conduct analysis?
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Question 28 of 61
28. Question
In DOE the principle of parsimony suggests that the goal of DOE is to use the minimum amount of data to discover the maximum amount of information?
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Question 29 of 61
29. Question
When two input factors are aliases of each other, the effects they each have on the response cannot be separated?
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Question 30 of 61
30. Question
A Resolution III DOE confounds its main effect with?
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Question 31 of 61
31. Question
A Resolution IV DOE confounds its main effect with?
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Question 32 of 61
32. Question
A Resolution V DOE confounds its main effect with?
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Question 33 of 61
33. Question
R2 is also referred to as the coefficient of determination?
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Question 34 of 61
34. Question
_________ is used to model the linear relationship between one output and two or more inputs?
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Question 35 of 61
35. Question
_______ are the vertical differences between actual values and the predicted values or the “fitted line” created by a regression model?
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Question 36 of 61
36. Question
When the variance inflation factor of an independent variable is larger than ______ there is large multicollinearity for this variable in the model?
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Question 37 of 61
37. Question
______ is the measure or quantifiable degree of confounding?
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Question 38 of 61
38. Question
What is the primary purpose of linear correlation analysis?
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Question 39 of 61
39. Question
Multiple linear regression is best described by which?
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Question 40 of 61
40. Question
What is the coefficient in this regression formula: Length = 3.5 + 1.29 mass
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Question 41 of 61
41. Question
Regression analysis does not rely on this assumption about the residuals
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Question 42 of 61
42. Question
When are correlation and linear regression not used?
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Question 43 of 61
43. Question
Which of the following statements is NOT correct?
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Question 44 of 61
44. Question
When is the degree of association Moderate?
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Question 45 of 61
45. Question
How is the transformation of nonnormal data into normal data done?
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Question 46 of 61
46. Question
What does a variance inflation factor (VIF) of 5 indicate?
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Question 47 of 61
47. Question
One factor at a time (OFAT) is a type of DOE
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Question 48 of 61
48. Question
Your multiple regression model returned 3 variables that were significant, and the model looks good based on all other measures. Of the 3 variables, which one has the most influence on your “Y?
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Question 49 of 61
49. Question
An interaction effect is the average change in the response variable resulting from changes in the levels of one factor?
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Question 50 of 61
50. Question
Interaction effect is the average change in the response resulting from the change in the interaction of multiple factors?
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Question 51 of 61
51. Question
Fractional factorials are less able to determine effects because of fewer degrees of freedom available to evaluate higher order interactions?
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Question 52 of 61
52. Question
Factor levels are the selected settings of a factor we are testing in the experiment
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Question 53 of 61
53. Question
_______ are the number of times running an individual treatment is repeated in a DOE?
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Question 54 of 61
54. Question
An experiment design is ________ if the main effect of one factor can be evaluated independent of other factors.
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Question 55 of 61
55. Question
_______is the quantification or degree of confounding in a DOE?
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Question 56 of 61
56. Question
The following descriptions is best matched with which DOE term; The Y or Dependent Variable or Process output measurement?
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Question 57 of 61
57. Question
The following descriptions is best matched with which DOE term; The change in the average response across two levels of a factor or between experimental conditions?
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Question 58 of 61
58. Question
The following descriptions is best matched with which DOE term; The X’s or Inputs or Independent variables?
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Question 59 of 61
59. Question
The following descriptions is best matched with which DOE term; Factor settings usually high and low, or + and , or 1 and 1
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Question 60 of 61
60. Question
Which of the following is a key advantage of DOE over passive learning?
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Question 61 of 61
61. Question
Statistical process control can be used in different phases of six sigma projects, such as before and after implementation of improvements?
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