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).

Predictor	Coefficient
Intercept	1,286.84
FloorSpace	13.87
CompetingAds	6.841
Price	0.1454

(a) Write the fitted regression equation. (Round your coefficient CompetingAds to 3 decimal places, coefficient Price to 4 decimal places, and other values to 2 decimal places. Negative values should be indicated by a minus sign.)

y^= _____________ + ___________ * FloorSpace + _____________ * CompetingAds + ______________ * Price

(d) Make a prediction for Sales when FloorSpace = 112, CompetingAds = 114, and Price = 1,386. (Enter your answer in thousands. Round your answer to 2 decimal places.)

Sales ________________ thousand