You Have Taken Over Your Parents' Small Dry-Cleaning Shop, and Are

You have taken over your parents' small dry-cleaning shop, and are interested in forecasting demand for your services. Your parents never quite got around to trying to measure demand, but they have kept extensive price and sales records. Using this data, you employ multiple regression techniques and estimate the following logarithmic equation:
Log(Q) = .95 − .6Log(P) + .9Log(Y) + .25Log(Pc),
where Q is the number of shirts laundered per week, P is the price in dollars of a laundered shirt, Y is the per capita income in the local area, and Pc is the price charged by another dry cleaner two blocks away. The number of observations is 39 (i.e., nine months of weekly data). The equation's R² is 0.85, the standard error of the estimate is 200, and the standard errors for the rightside variables are .45, .15, .39, and .18 respectively.
(a) Interpret the demand equation and discuss the associated regression statistics.
(b) If you were to raise the price per shirt, what would happen to total revenue?
(c) Evaluate the impact of the other dry cleaner’s price on your sales. (At the 95% confidence level, the relevant t-statistic is about 2.04 for 35 degrees of freedom).
(d) Were your parents maximizing profit? If not, suggest an appropriate course of action to
increase profitability