Question

You work for a snow cone company. You've collected data on monthly sales (S, number of snow-cones per month) and the price of your regular-size snow-cone (P, in dollars), as well as the daily average summer temperature in your most popular market (T, in degrees Fahrenheit). You estimate the following regression model:

S = a + bP + cT.

In your regressions, you usually look for a 10%-or-better level of confidence.

a)  What are the expected signs for a, b, and c?

Your regression yields the following results:

Adjusted R Square              0.883                                                                     

Independent Variables      Coefficients   Standard Error   t Stat          P-value

Intercept                                2718                598                4.544           0.00615

P                                           -641.62            90.23              -7.111        0.00085

T                                           10.32               6.36                 1.623        0.16562

  

b) The estimated coefficient for a (intercept) suggests that?

c) The estimated coefficient for b (price of the regular size snow-cone) suggests that?

d) The estimated coefficient for c (daily average summer temperature) suggests that?

e) The price of the regular size snow-cone has a statistically significant effect on our sales? True or False

f) Daily average summer temperature affects the sales of regular size snow-cones in a statistically significant way? True or False

g) What portion of the total variation in sales of the regular size snow-cone remains unexplained?

h) The snow cone company is considering selling in a new city, where the average daily summer temperature is 83°, for a price of $4.10. What level of sales would you expect in this new city (rounded to the nearest unit)?

Answer 1