# Question: Observations are taken on sales of a certain mountain bike

Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The regression model was Y = total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised price (dollars per unit).

(a) Write the fitted regression equation.

(b) Interpret each coefficient.

(c) Would the intercept seem to have meaning in this regression?

(d) Make a prediction for Bikes Sales when FloorSpace = 80, CompetingAds = 100, and Price = 1,200.

(a) Write the fitted regression equation.

(b) Interpret each coefficient.

(c) Would the intercept seem to have meaning in this regression?

(d) Make a prediction for Bikes Sales when FloorSpace = 80, CompetingAds = 100, and Price = 1,200.

## Relevant Questions

The same data set from exercise 13.19 also has gender information for each engineer. The binary variable Male = 1 indicates the engineer is male and Male = 0 indicates the engineer is female. Run the regression with Salary ...State your a priori hypotheses about the sign (1 or 2) of each predictor and your reasoning about cause and effect. Would the intercept have meaning in this problem? Explain. (a) Generate a correlation matrix for your predictors. Round the results to three decimal places. (b) Based on the correlation matrix, is collinearity a problem? What rules of thumb (if any) are you using? A hospital emergency room analyzed n = 17,664 hourly observations on its average occupancy rates using six binary predictors representing days of the week and two binary predictors representing the 8-hour work shift (12 ...Refer to the ANOVA table below. (a) State the degrees of freedom for the F test for overall significance. (b) Use Appendix F to look up the critical value of F for α = .05. (c) Calculate 2 the F statistic. Is the ...Post your question