Customer Satisfaction. Due to high competition among the restaurants in a commercial area, a newly opened restaurant conducts a short survey to find out its customers’ satisfaction regarding their dining experience at the restaurant. The restaurant would like to determine a regression model on the amount customers spent by considering the following variables:

Gender 1 if male, 0 otherwise Peak Hours 1 if dining during peak hours, 0 otherwise Waiters/

Environment 1 if satisfied on their waiters/waitress’s services, 0 otherwise Food 1 if satisfied on their foods, 0 for the other Waiting Time 1 if satisfied on the waiting time of getting a table and food to be served, 0 otherwise Here’s the regression.

Dependent variable is: amount customers spent R-squared = 0.5105, Adjusted R-squared: 0.4406 SE = 34.1315 with 41 observations Variable Coefficient SE(Coeff) t-ratio P-value Intercept 2.0148 20.1580 0.1000 0.9210 Gender 25.1871 11.2520 2.2385 0.0317 Peak Hours -28.0236 11.5042 -2.4359 0.0201 Waiters/

Environment 42.5564 19.6931 2.1610 0.0376 Food 53.7003 18.8433 2.8498 0.0073 Waiting Time 26.2753 11.5422 2.2765 0.0290

a) All these predictors are of a special kind. What are they called?

b) What is the interpretation of the coefficient for Waiting Time?

c) The restaurant owner most concerned on the waiting time effect on the amount spent by customers, why is it important, and how other variables effects the model?

d) Based on this regression, besides the waiting time, what could you report to the restaurant owner on his customers’

expenses in his restaurant?