Disposable income variable being added Summary measures % Change Multiple R 0.9608 1.0% R-Square 0.9232 2.0% Adj R-Square 0.9130 1.6% StErr of Estimate 3643.11 -7.2% Average price variable being added Summary measures % Change Multiple R 0.9723 1.2% R-Square 0.9454 2.4% Adj R-Square 0.9337 2.3% StErr of Estimate 3179.03 -12.7% Regression coefficients Coefficient Std Err t-value p-value Constant -73971.53 23803.23 3.1076 0.0077 Monthly Adv. Expenditures 0.952 0.375 2.5387 0.0236 Disposable Income 2.606 0.977 2.6659 0.0184 Average Price -2056.27 861.342 -2.3873 0.0316 4. Choose all the correct statements for a 0.10 significance level. (Use chart above for only question #4) The regression coefficient for monthly advertising expenditures is significant The regression coefficient for monthly advertising expenditures is significant The regression coefficient for average price is significant As monthly advertising expenditures increases, sales increase As Disposable Income increases, sales increase As average price increases, sales increase 5. If a regression model contains a variable for Gender with two options --Male and Female, how many dummy variables are required? 6. If a regression model for the prediction of salaries is Y = 30,000 + 5000 X, where X represents Gender. X= 1 for Males and X = 0 for females. What is the implication of the regression coefficient? C Males earn on average $5000 more than Females C On average, Females earn $5000 more than Males11. A researcher is trying to predict annual salary for GA, SC, and TN using the following model where X1 = 1, if GA resident; X2=1, if SC resident. Y = 30000 - 500 X1 - 700 X2 Which state has the highest average salary? Select all the true statements below. TN residents have the highest averagesalary. GA residents have the highest average salary SC residents have the highest average salary. GA and SC residents have lower average salaries than TN The average salary for TN residents is 30,000 To determine the difference in the average salary for GA and TN, the regression cofficients can be compared.. Since both regression coefficients are negative, GA and SC have lower average salaries than TN. If the regression coefficient for X2 were positive $700 instead of -$700, it can be concluded that SC has a larger average salary than GA. Another variable should be added to this model. X3 = 1 if TN resident. If both regression coefficients were positive instead of negative, we can conclude that TN has the highest average salary. 12. A researcher is trying to predict annual salary for the following states -- FL, NC, VA with the regression model: Y = 30,000 + 200 X1 -400 X2 where X1 = if FL resident and X2 = 1 if VA resident. What is indicated by the value of the regression coefficients? C NC has the highest average salary C FL has the highest average salary C VA has the highest average salary7. A researcher is trying to predict annual salary for the following states: AL, MS and LA. How many dummy variables are required I 8. A researcher is trying to predict annual salary for AL, LA and MS with the regression model: Y = 30,000 + 2000 X1 -400 X2 where X1 = 1 if AL resident and X2 = 1 if MS resident. What is the value of the expected salary for AL residents? l 9. A researcher is trying to predict annual salary for AL, MS, and LA With the regression model: Y = 30,000 + 2000 X1 400 X2 where X1 =1 if AL resident and X2 = if MS resident. What is the value of the expected salary for MS residents? l 10. A researcher is trying to predict annual salary for AL, MS, and LA states with the regression model: Y = 30,000 + 2000 X1 -400 X2 where X1 = if AL resident and X2 = if MS resident. What is the value of the expected salary for LA residents? l Regression Review The owner of a pizza restaurant chain would like to predict the sales of her specialty, the deep-dish Mexican pizza. She has gathered data on monthly sales of the deep-dish Mexican pizza at her restaurants. She has also gathered information related to the average price of the deep-dish pizzas, the monthly advertising expenditures and the disposable income per household in the areas surrounding the restaurants. Below you will find output from the stepwise regression analysis. The p-value method was used with a cutoff of 0.05. Summary measures Multiple R 0.9513 R-Square 0.9049 Adj R-Square 0.8990 StErr of Estimate 3924.53 Regression coefficients Coefficient Std Err t-value p-value Constant 45233.64 8914.72 -5.0740 0.0001 Monthly Adv. Expenditures 1.972 0.160 12.3405 0.0000 1. What is the value of the regression coefficient? C 9513 C 9049 C -45233.64 C 1.972 2. What percentage of variation in sales can be explained by the variation in monthly advertising expenditures? C 95.13 C 90.49 3. At the 0.05 level of significance is the regression coefficient significant? C Yes because p-value is less than alpha C Yes because the p-value is greater than alpha C No because the p-value is less than alpha C No because the p-value is greater than alpha