Regression approach to forecast Coke’s sales.

Suppose a grocery store manager uses the regression approach to forecast Coke’s sales. He sets ‘Coke sale’ as the dependent variable, and ‘Coke Price’ and ‘Pepsi Price’ as the independent variables as follows: Coke sales = Beta0 + Beta1 * Coke Price + Beta2 * Pepsi Price He has the weekly data on Coke sales, Coke Price and Pepsi Price of last year, and the regression result proves that this linear model fits the data very well. The results are as follows: Beta0 = 120; Beta1 = – 60; Beta2 = 25 Suppose the store manager decides to reduce Coke’s price from $2 per unit to $1.8 per unit, and keeps Pepsi price at $2. The overall effect on Coke would be that Coke sales would _________

A. increase 5 units

B. decrease 5 units

C. decrease 12 units

D. increase 12 units

E. increase 17 units