A simple linear regression of the return of firm A ( RA) on the return of firm B ( RB) based on 18 observations, is KA = 2.2 + 0.4 R B. If the coefficient of determination from this regression is 0.09, calculate the correlation between nR A and RA. O 0.03 O 0.04 O 0.09 O 0.30A sociologist examines the relationship between the poverty rate and several socioeconomic factors. For the 50 states and the District of Columbia ( n = 51), he collects data on the poverty rate (y, in %), the percent of the population with at least a high school education (X1), median income ( X2, in $10005), and the mortality rate per 1,000 residents (X 3). He estimates the following model as y: ,8 0 + [31 Education + B 2 Income + B 3 Mortality + a. The following ANOVA table shows a portion of the regression results. df SS MS F Regression Residual _ Total _ Intercept 1-65E-16 Education 5-45E-10 Income 6-02E-10 Mortality 0-6438 Which of the following is the value of the mean square error, (MSE)? O 0 O 4.5 C) 1.5 O 3.0 A study was recently conducted by Major League Baseball to determine whether there is a correlation between attendance at games and the record of home team's opponent. In this study, the dependent variable would be the record of the home team's opponent. True O False A study was recently done in which the following regression output was generated using Excel. SUMMARY OUTPUT Regression Statistics Multiple R 0.754525991 R Square 0.569309472 Adjusted R Square 0.507782253 Standard Error 1.977472261 Observations 9 ANOVA df SS MS F Significance F Regression 36.18277975 36.18278 9.252969 0.018797 Residual 27.3727758 3.910397 Total 8 63.55555556 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 4.822953737 2.20457789 2.187699 0.064899 -0.39004 10.03595 X 0.053825623 0.017694916 3.041869 0.018797 0.011984 0.095667 Given this output, we would reject the null hypothesis that the population regression slope coefficient is equal to zero at the alpha = 0.05 level. O True O FalseA study was recently performed by the Internal Revenue Service to determine how much tip income waiters and waitIesses should make based on the size of the bill at each table A random sample of bills and resulting tips were collected and the following regression results were observed: SUMJVIARY OUTPUT Rc ssion Statistiw Multiple R 0936647585 R Square 0877308695 Adjusted R Square 0861972285 Standard Error 3509074782 Observations 10 ANOVA 55 MS F Regression 1 704.39] 15.34 704.3912 57.2043 Residual 8 985088466 12.31361 Total 9 802.9 Cu 5:an Standard Emir t Stat P-valm' Intercept -0.668419699 2.020239042 -0.33086 0.749248 Total Bill 0212806995 0.028136597 7.563352 6.53E05 Given this output, the point estimate for the change in tip per dollar amount of the bill is approximately $0.21 True O False An marketing analyst wants to examine the relationship between sales (in $1,0005) and advertising (in $1005) for firms in the food and beverage industry and collects monthly data for 25 firms. He estimates the model: Sales: [3 0 + ,81 Advertising + s. The following ANOVA table below shows a portion of the regression results. Standard Error Intercept 14.08 2.848 0.0052 Advertising -1-895 0.0608 Which of the following is the prediction of Sales for a firm with Advertising of $500? 0 $40,100 0 $54,500 $1,480 0 $148,000 Assume you ran a multiple regression to gain a better understanding of the relationship between lumber sales, housing starts, and commercial construction. The regression uses lumber sales (in $100,000s) as the response variable with housing starts (in 10005)(in 1,000s) and commercial construction (in 10005)(in 1,0005) as the explanatory variables. The estimated model is Lumber Sales = ,8 0 + ,61 Housing Stan's + ,8 2 Commercial Constructions + c. The following ANOVA table summarizes a portion ofthe regression results. -m_m- Commercial Construction 1.25 0.33 3.78 0.0005 If Housing Starts were 17,000 and Commercial Construction was 3,200, the best estimate of Lumber Sales would be $22,290,000 0 $16,920,000 0 $16,925,370 0 $22,014,000 Based on the partially completed ANOVA table below, we know that 3 groups are being compared using 9 observations 387 422 ____ 1374 __ 0 True False Both a scatter plot and the correlation coefficient can distinguish between a curvilinear and a linear relationship. O True O FalseComputer, the correlation coefficient, rounded to the nearest thousandth, for the following data: X 9 7 2 6 5 11 4 V 7 9 15 8 11 7 14 0.905 O -0.75 O -0.905 O 0.75