SECTION A-MULTIPLE CHOICE QUESTIONS 1. One of the assumptions in regression analysis is that a. the errors have a mean o

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SECTION A-MULTIPLE CHOICE QUESTIONS 1. One of the assumptions in regression analysis is that a. the errors have a mean of 1. b. the errors have a mean of 0. c. the observations (Y) have a mean of 1. d. the observations (Y) have a mean of 0. variable, the number of dummy variables should equal to a. the number of categories. b. one more than the number of categories. c. one less than the number of categories. d. the number of other independent variables in the model. 2. A graph of the sample points that will be used to develop a regression line is called a. a sample graph. b. a regression diagram. c. a scatter diagram. d. a regression plot. 9. A multiple regression model differs from a simple linear regression model because the multiple regression model has more than one a. independent variable. b. dependent variable. c. intercept. d. error. 3. When using regression, an error is also called a. an intercept. b. a prediction c. a coefficient d. a residual. 10. The overall significance of a regression model is tested using an F test. The model is significant if a. the F value is low. b. the significance level of the F value is low. c. the value is low. d. the slope is lower than the intercept. 4. In a regression model, Y is called a. the independent variable. b. the dependent variable. c. the regression variable. d. the predictor variable. 11. A new variable should not be added to a multiple regression model if that variable causes a. to decrease. b. the adjusted to decrease. c. the SST to decrease. d. the intercept to decrease. measure of how far 1? A good regression model should have al for the F test

5. A quantity that provides a measure of how far each sample point is from the regression line is a. the SSR b. the SSE. c. the SST. d. the MSR. 12. A good regression model should have a. a low and a low significance level for the F test. b. a high and a high significance level for the F test. c. a high and a low significance level for the F test. d. a low 12 and a high significance level for the F a test. 6. The percentage of the variation in the dependent variable that is explained by a regression equation is measured by; a. the coefficient of correlation. b. the MSE. c. the coefficient of determination. d. the slope. 7. In a regression model, if every sample point is on the regression line (all errors are 0), then a. the correlation coefficient would be 0. b. the correlation coefficient would be -1 or 1. c. the coefficient of determination would be -1. d. the coefficient of determination would be 0. 8. When using dummy variables in a regression equation to model a qualitative or categorical

SECTION B - QUESTION 1: a) What is an ANOVA test? b) In 2009, the New York Yankees won 103 baseball games during the regular season. The table on the next page lists the number of victories (W), the earned run-average (ERA), and the batting average (AVG) of each team in the American League. The ERA is one measure of the effectiveness of the pitching staff, and a lower number is better. The batting average is one measure of effectiveness of the hitters, and a higher number is better. (1) Develop a regression model that could be used to predict the number of victories based on the ERA. (ii) Develop a regression model that could be used to predict the number of victories based on the batting average. (iii) Which of the two models is better for predicting the number of victories? (iv) Develop a multiple regression model that includes both ERA and batting average. How does this compare to the previous models?

TEAM W BRA AVG New York Yankees 103 4.26 0.283 97 4.45 0.285 Los Angeles Angels Boston Red Sox Minnesota Twins 95 4.35 0.270 87 4.50 0.274 87 4.38 0.260 Texas Rangers Detroit Tigers 86 4.29 0.260 Seattle Mariners 85 3.87 0.258 84 4.33 0.263 79 4.14 0.258 Tampa Bay Rays Chicago White Sox Toronto Blue Jays Oakland Athletics 75 4.47 0.266 75 4.26 0.262 Cleveland Indians 65 5.06 0.264 Kansas City Royals 65 4.83 0.259 Baltimore Orioles 64 5.15 0.268