test 3 fall - QUESTIONS 1-4: To gauge how your firms...

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To gauge how your firm’s advertising and other promotional activities affect your firm’s sales, you collected data on your firm’s sales (in thousands of dollars) for 51 months and the firm’s promotional expenditures (in thousands of dollars. Graphs and statistics support the regression model: Sales = 25.1264 + 0.7623PromoExpend . 1. To test whether the simple linear model is useful, we test a. Whether the y-intercept is different from 0. b. Whether the y-intercept is different from 1. c. Whether r 2 is large. d. Whether the slope parameter is different from 0. e. Whether the slope parameter is different from 1. 2. Which of the following is a correct interpretation of the parameter estimates? a. As sales increase by $1, promotional expenditures increase on average by $25.12. b. As promotional expenditures increase by $1000, sales increase on average by $762.30. c. As promotional expenditures increase by $1000, sales decrease on average by $762.30 d. When promotional expenditures are $0, sales are predicted to be $25,126.40 per month on average. e. When sales are $0, promotional expenditures are predicted to be $25.12 during that month on average. 3. If the standard error of b 1 (s b1 ) = 0.1209, which of the following is correct? a. We are 95% confident that as sales increase by $1, promotional expenditures increase on average between $1.23 to $49.02. b. We are 95% confident that as promotional expenditures increase by $1000, sales increase on average between $519.40 and $1005.20. c. We are 95% confident that as promotional expenditures increase by $1, sales decrease on average between $0.52 and $1.01. d. We are 95% confident that as sales increase by $1, promotional expenditures increase on average between $519.40 and $1005.20. 4. If r = 0.673, which of the following is correct? a. The correlation between sales and promotional expenditures is 0.4529. b. If we use the model to predict, we can expect 45.29% of our actual sales values to be within one standard error of their predicted values. c. We get 45.29% more prediction error by simply using the sample average to predict sales, rather than using the model to predict sales. d. 45.29% of the variability in monthly sales can be explained by monthly promotional expenditures. e.
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test 3 fall - QUESTIONS 1-4: To gauge how your firms...

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