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Multiple Regression Quiz 1 (25 MCQs)

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1. What test statistic is used for a global test of significance?
2. To detect multicollinearity a researcher should
3. Variable Selection Methods are helpful when
4. Suppose that we want to test the overall significance of the regression model Y=$\beta$0+$\beta$1X1+$\beta$2X2+$\beta$3X3+$\beta$4X4+$\beta$5X5+u with 100 observations. Which one correctly defines the test statistic for this hypothesis?
5. The most popular variable selection method is
6. The partial F-test
7. Consider the null hypothesis H0:$\beta$1=0, $\beta$2=2$\beta$3, $\beta$3=2$\beta$4=2 for the model:Y=$\beta$0+$\beta$1X1+$\beta$2X2+$\beta$3X3+$\beta$4X4+$\beta$5X5+u. Which one is the restricted model for this null?
8. Polynomial regression, specifically with a quadratic term
9. The percent of total variation of the dependent variable Y explained by the set of independent variables X is measured by
10. Which one is correct about hypothesis test?
11. Variable selection methods generally work by selecting IVs in a sequential fashion based on _____
12. If the Pearson correlation co-efficient R is equal to 1 then
13. When an interaction is significant, what is the researcher's next step? Evaluate
14. In the equation of a straight line, Y = mX + c, if m is equal to-2 then
15. Data on some variables might contain a classification (e.g., defective or good, graduate or undergraduate, etc.) rather than numerical values. Such variables are referred to as _____
16. When will you use hierarchical entry regression? When
17. The data on a variable x contains a series of numerical values (all > 1). If we create a new variable z = 1/x, the numerical values of the new variable z when compared those of x will _____
18. A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland and Yorktown), and production shift (day and evening). The response variable in this model is _____
19. In regression analysis, a dichotomous variable, i.e., a variable which stands for one of two possible categories of an observation (e.g., male or female), is assigned a value of _____
20. A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighbourhood (urban, suburban, and rural). The response variable in this model is _____
21. In the equation of a straight line, Y = mX + c, if m is equal to zero then when
22. Matrix algebra is important because
23. Which parameter estimate is the location parameter?
24. When you have categorical predictors, the intercept is the
25. In regression analysis, outliers may be identified by examining the _____ a) coefficient of determinationb) coefficient of correlationc) p values for the partial coefficientsd) residualse) R-squared valueAnswer:d
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