Question

c, g, and h

1. A fast-food restaurant chain is interested in modeling the mean weekly sales (measured in thousands of $) of a restaurant as a function of the weekly traffic flow on the street (measured in thousands of cars) where the restaurant is located and the city in which the restaurant is located. The table below contains the data on 24 restaurants in 4 cities. The independent variables are defined as follows: X, = traffic flow X2 = 1 if Jonestown, O otherwise X3 = 1 if Mayberry, 0 otherwise X = 1 if Smithson, 0 otherwise No variable is included for Rockville, the 4th city. This is a partial printout from the computer. Intercept FLOW Jonestown Mayberry Smithson Coefficients 1.083387561 0.103673352 -1.2157616 -0.53075677 -1.07652473 Standard Errort Stat P-value 0.321007955 3.374955 0.003179 0.00409449 25.32021 4.21E-16 0.205386814 -5.91938 1.07E-05 0.284819464 -1.86348 0.077925 0.226500138 -4.75287 0.000138

Answer 1

(c) The p-value from the output is 0.0000.

Since the p-value (0.0000) is less than the significance level (0.01), we can reject the null hypothesis.

Therefore, we have sufficient evidence to conclude that higher traffic flows lead to an increase in weekly sales.

(g) The regression equation is:

Sales = 1.08 + 0.10*Flows -1.22*Jonestown -0.53*Mayberry -1.08*Smithson

Sales = 1.08 + 0.10*65000

= 6501.08

(h) 72%

Please give me a thumbs-up if this helps you out. Thank you!