QUESTION 16 An marketing analyst wants to examine the relationship between sales (in $1,000s) and advertising (in $100s) for firms in the food and beverage industry and collects monthly data for 25 firms. He estimates the model: Sales= Bo+ B 1 Advertising + E. The following ANOVA table below shows a portion of the regression results. df SS MS F Regression 1 78.53 78.53 3.58 Residual 23 504.02 21.91 Total 24 582.55 Coefficients Standard Error t-stat p-value Intercept 40.1 14.08 2.848 0.0052 Advertising 2.88 1.52 -1.895 0.0608 Which of the following is the prediction of Sales for a firm with Advertising of $500? O $40,100 O $1,480 O $148,000 O $54,500QUESTION 21 Consider the following partially completed computer printout for a regression analysis where the dependent variable is the price of a personal computer and the independent variable is the size of the hard drive. SUMMARY OUTPUT Regression Statistics Multiple R 0.819361805 R Square Adjusted R Square 0.661687702 Standard Error Observations 36 ANOVA of SS MS F Significance F Regression 1 33116034.84 33116034.84 Residual 16211214.72 Total 35 49327249.56 Coefficients Standard Error 1 Stat P-value Intercept 50.84102383 246.9869514 0.205844979 0.838139607 Hard Drive Capacity 217.7539792 26.12854674 9.95844E-10 Based on the information provided, which of the following statements is true if alpha = 05? The slope is not significantly different from 0 because p-value = 9.95 is greater than 0.05 The slope is significantly different from 0 because p-value = 9.95En - 10 is less than 0.05 The slope is not significantly different from 0 because p-value = 0.84 is greater than 0.05 The slope is significantly different from 0 because p-value = 9.95 is greater than 0.05QUESTION 38 Solve the problem. Use the following data to a. determine the coefficient of correlation, rounded to the nearest thousandth, b. find the equation of the regression line for time watching TV and time on the Internet, c. approximate how much time on the Internet can we predict for a person who spends 10 hours weekly watching TV. Subject ABCDEFG Time watching TV 13 9 7 12 12 10 11 Time on Internet 14 12 8 17 18 9 18 a. r= -0.752 b. y = -1.52x - 2.35 c. 17.5 hours O a. r = -0.752 b. y = -2.35x + 1.52 c. 22 hours O a. r = 0.752 b. y = 1.52x - 2.35 c. 12.9 hours O a. r = 0.752 b. y = 1.52x + 2.35 c. 17.6 hoursQUESTION 4 A hotel chain has four hotels in Oregon. The general manager is interested in determining whether the mean length of stay is the same or di event for the four hotels. She selects a random sample of n = 20 guests at each hotel and determines the number of nights they stayed. Assuming that she plans to test this using an alpha level equal to 0.05, which of the following is the appropriate alternative hypothesis? 0 H0411 #uzipaim H0411 =u2 =p3=u4 O Not all population means are equal. 0 51:02:03=04 QUESTION 42 The R2 ofa multiple regression of yon x 1 and x 2 measures the 0 percent variability of y that is explained by the variability of x1 and x2 @ percent variability of y that is explained by the variability of x2 0 percent variability of y that is explained by the variability of x1 0 statistical signicance of the coefcients in the regression equation QUESTION 43 Unlike the coefficient of determination, the coefficient of correlation in a simple linear regression measures the strength of association between the two variables more exactly 0 can never have an absolute value greater than 1 0 indicates whether the slope of the regression line is positive or negative 0 measures the percentage of variation explained by the regression line QUESTION 45 Use the following regression :esulE to answer the question below. R let-aim Shari-11b: Multiple R 0.8851 R Square 0.7835 Adjus ted R Square 0.7474 Standard Error 5.4006 Observations 8 ANOVA 55 MS F Regression 1 633.242 633.242 21.711 Residual 6 175.000 29.167 Total 7 $8.242 C1 rent-e Standard Ermr E Stat 35min: Intercept 5.93113 4.17721 1.41989 020545 Total Bill -2.7155l 0.58279 4.65952 0.00347 Which of the following is true? @ The correlation between x and 3! must be approximately 41835]. O The correlation between x and 3! must be approximately 0.?335. 0 The correlation between x and 3! must be approximately 0.7335. 0 The correlation between X and ymust be approximately 0.8351