The data come from three different servers, coded as A, B, and C, and we also have information on whether or not a credit (or debit) card was used to pay the bill rather than cash. The frequency counts are shown in the two-way table in Table D.7. At a 5% significance level, is there an association between who the server is and whether the bill is paid in cash or with a credit/debit card?

Table D.7

In Data 2.12 on page 119, we introduce the dataset RestaurantTips containing information on the tipping patterns of patrons of the First Crush bistro in northern New York state. The data from 157 bills include the amount of the bill, size of the tip, percentage tip, number of customers in the group, whether or not a credit card was used, day of the week, and a coded identity of the server. The first four variables are quantitative and the last three are categorical.

Data 2.12 on page 119

The owner of a bistro called First Crush in Potsdam, New York, is interested in studying the tipping patterns of its patrons. He collected restaurant bills over a two-week period that he believes provide a good sample of his customers. The data from 157 bills are stored in RestaurantTips and include the amount of the bill, size of the tip, percentage tip, number of customers in the group, whether or not a credit card was used, day of the week, and a coded identity of the server.

Total Server A B 39 21 Cash 50 15 17 106 Card 15 51 65 32 157 Total 60