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.

Transcribed Image Text:

Predictor Coefficient 1225.44 Intercept FloorSpace CompetingAds Price 11.52 -6.935 -0.1496