Use the following regression analysis to answer the questions below. The dependent variable is the number of tickets sold per week, and the independent variables are the price of the flight (X1) measured in dollars; the price of the competitor’s ticket (X2) measured in dollars; GDP (X3) measured in thousands of dollars; the general season of the year (X4) measured as a 0 for summer and a 1 for winter; the price of automotive gasoline (X5) measured in cents per gallon (consider driving as a substitute for flying in this regression); and the local population in thousands (X6). The “t” statistic is given in parenthesis below the independent variable (use a “t” value of 2 for a 95% confidence level and consider this significant).

Y = 300 – 15 X1 + 2 X2 + 25 X3 − 150 X4 + 30 X5 + 5X6 R-squared = 0.85 “t” value= (3) (2) (4) (2.5) (1.0) (2)

a. What is the most statistically significant independent variable in the regression?

b. According to this equation, how does winter affect the number of tickets sold?

c. Does the price of gasoline in the equation have the correct sign?

d. Suppose that competitors reduce their price by $20 and there is a population growth of 2000 at the same time. What will happen to the number of tickets sold?