TRUE/FALSE. Write 'T' if the statement is true and 'F' if the statement is false. 1) A scatter plot is used to visualize the association (or lack of association) between two quantitative variables. 1) 2) The fitted intercept in a regression has little meaning if no data values near X = 0 have been observed. 2) 3) The F statistic in a multiple regression is significant if at least one of the predictors has a significant t statistic at a given . 3) 4) R2adj can exceed R2 if there are several weak predictors. 4) MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 5) The standard error of the regression: A) may be cut in half to get an approximate 95 percent prediction interval. B) is based on squared deviations from the regression line. C) may assume negative values if b1 < 0. D) is in squared units of the dependent variable. 5) 6) If the attendance at a baseball game is to be predicted by the equation Attendance = 16,500 - 75 Temperature, what would be the predicted attendance if Temperature is 90 degrees? A) 10,020 B) 9,750 C) 6,750 D) 12,250 6) 17) A researcher's Excel results are shown below using Femlab (labor force participation rate among females) to try to predict Cancer (death rate per 100,000 population due to cancer) in the 50 U.S. states. Which of the following statements is not true? A) The standard error is too high for this model to be of any predictive use. B) The two-tailed p-value for Femlab will be less than .05. C) Significant correlation exists between Femlab and Cancer at = .05. D) The 95 percent confidence interval for the coefficient of Femlab is -4.29 to -0.28. 7) 8) A researcher's results are shown below using Femlab (labor force participation rate among females) to try to predict Cancer (death rate per 100,000 population due to cancer) in the 50 U.S. states. What is the R2 for this regression? A) .0982 B) .1605 C) .8395 D) .9018 8) 9) In a simple regression, which would suggest a significant relationship between X and Y? A) Large t statistic for the slope. B) Small t statistic for the slope. C) Large p-value for the estimated slope. D) Large p-value for the F statistic. 9) 210) Simple regression analysis means that: A) we have only one explanatory variable. B) there are only two independent variables. C) we have only a few observations. D) the data are presented in a simple and clear way. 10) 11) Which is not an assumption of least squares regression? A) Normal errors B) Non-autocorrelated errors C) Normal X values D) Homoscedastic errors 11) 12) In a sample of size n = 23, a sample correlation of r = .400 provides sufficient evidence to conclude that the population correlation coefficient exceeds zero in a right-tailed test at: A) neither = .05 nor = .01. B) = .05 but not = .01. C) both = .05 and = .01. D) = .01 but not = .05. 12) 13) A local trucking company fitted a regression to relate the cost of its shipments as a function of the distance traveled. The Excel fitted regression is shown. Based on this estimated relationship, when distance increases by 50 miles, the expected shipping cost would increase by: A) $104. B) $286. C) $143. D) $301. 13) 314) A test is conducted in 22 cities to see if giving away free transit system maps will increase the number of bus riders. In a regression analysis, the dependent variable Y is the increase in bus riders (in thousands of persons) from the start of the test until its conclusion. The independent variables are X1 = the number (in thousands) of free maps distributed and a binary variable X2 = 1 if the city has free downtown parking, 0 otherwise. The estimated regression equation is . In city 3, the observed Y value is 7.3, X1 = 140, and X2 = 0. The residual for city 3 (in thousands) is: A) 4.83. B) 6.15. C) 1.57. D) 1.15. 14) 15) Which of the following is not true of the standard error of the regression? A) It is used in constructing confidence and prediction intervals for Y. B) It would be negative when there is an inverse relationship in the model. C) It is a measure of the accuracy of the prediction. D) It is based on squared vertical deviations between the actual and predicted values of Y. 15) 16) A multiple regression analysis with two independent variables yielded the following results in the ANOVA table: SS(Total) = 798, SS(Regression) = 738, SS(Error) = 60. The multiple correlation coefficient is: A) .2742 B) .9248 C) .9617 D) .0752 16) 17) Using a sample of 63 observations, a dependent variable Y is regressed against two variables X1 and X2 to obtain the fitted regression equation Y = 76.40 - 6.388X1 + 0.870X2. The standard error of b1 is 3.453 and the standard error of b2 is 0.611. At = .05, we could: A) conclude that both coefficients differ significantly from zero. B) reject H0: 2 0 and conclude H0: 1 > 0. C) conclude that Evans' Rule has been violated. D) reject H0: 1 0 and conclude H0: 1 < 0. 17) 418) Refer to this ANOVA table from a regression: Which statement is not accurate? A) The F-test is significant at = .05. B) There were 5 predictors. C) There were 50 observations. D) There would be 50 residuals. 18) 19) Refer to the following regression results. The dependent variable is Abort (the number of abortions per 1000 women of childbearing age). The regression was estimated using data for the 50 U.S. states with these predictors: EdSpend = public K-12 school expenditure per capita, Age = median age of population, Unmar = percent of total births by unmarried women, Infmor = infant mortality rate in deaths per 1000 live births. Which statement is not supported by a two-tailed test? A) Infmor is not a significant predictor at = .05. B) Unmar is a significant predictor at = .01. C) Age is not a significant predictor at = .05. D) EdSpend is a significant predictor at = .20. 19) 20) In a multiple regression all of the following are true regarding residuals except: A) they may be used to detect multicollinearity. B) their sum always equals zero. C) they are the differences between observed and predicted values of the response variable. D) they may be used to detect heteroscedasticity. 20) 5