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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 Sales when FloorSpace = 80, CompetingAds = 100, and Price = 1,200.

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

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