The following is the partial printout of problem "The Fresh Detergent Case": Enterprise Industries produces Fresh, a bra
Posted: Wed May 11, 2022 2:09 pm
The following is the partial printout of problem "The Fresh Detergent Case": Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to manage its inventory more effectively and make revenue projections, the company would like to better predict demand for Fresh. To develop a prediction model, the company has gathered data concerning demand for Fresh over the last 30 sales periods (each sales period is defined to be a four- week period). Here are the variables that will be in the model: Y= the demand for the large size bottle of Fresh (in hundreds of thousands of bottles) in the sales period. X1=the price (in dollars) of Fresh as offered by Enterprise Industries in the Sales period. X2-the average industry price in dollars) of competitors' similar detergents in the sales period. X3=Enterprise Industries' advertising expenditure (in hundreds of thousands of dollars) to promote Fresh in the sales periods. The figure below provides the output of the multiple regression model from the Excel:
SUMMARY OUTPUT 0.945 Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.881 30 ANOVA df SS MS Significance F Regression Residual Total 1.432 13.459 Stat 3.104 P-value 0.005 Intercept Price IndPrice AdvExp Coefficients 7.589 -2.358 1.612 0.501 Standard Error 2.445 0.638 0.295 0.126 5.459 3.981 0.000 0.000
Question 12 1 pts In multiple linear regression, the adjusted R square helps us balance the number of the independent variables and the Rsquare. True False D Question 13 1 pts Please use three decimal places. What is the predicted demand for Fresh if the price is 3.5, IndPrice is 3.9, and the average expenditure is 6.5? O 1.290 O 8.879
Question 14 1 pts What is the correct interpretation of the coefficient of Pricel-2.358)? When Price increases by 1 dollar, the demand for the large size bottle decreases by 2,358 bottles. o When Price increases by 1 dollar, the demand for the large size bottle Increases by 2,358 bottles O When Price increases by 1 dollar, the demand for the large size bottle decreases by 235800 bottles. O When Price increases by 1 dollar and the other variables hold constant values, the demand for the large size bottle decreases by 235800 bottles.
SUMMARY OUTPUT 0.945 Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.881 30 ANOVA df SS MS Significance F Regression Residual Total 1.432 13.459 Stat 3.104 P-value 0.005 Intercept Price IndPrice AdvExp Coefficients 7.589 -2.358 1.612 0.501 Standard Error 2.445 0.638 0.295 0.126 5.459 3.981 0.000 0.000
Question 12 1 pts In multiple linear regression, the adjusted R square helps us balance the number of the independent variables and the Rsquare. True False D Question 13 1 pts Please use three decimal places. What is the predicted demand for Fresh if the price is 3.5, IndPrice is 3.9, and the average expenditure is 6.5? O 1.290 O 8.879
Question 14 1 pts What is the correct interpretation of the coefficient of Pricel-2.358)? When Price increases by 1 dollar, the demand for the large size bottle decreases by 2,358 bottles. o When Price increases by 1 dollar, the demand for the large size bottle Increases by 2,358 bottles O When Price increases by 1 dollar, the demand for the large size bottle decreases by 235800 bottles. O When Price increases by 1 dollar and the other variables hold constant values, the demand for the large size bottle decreases by 235800 bottles.