**12.43** In Problem 12.5 on page 441, you used the summated rating of a restaurant to predict the cost of a meal. The data are stored in RESTAURANTS ATTACHMENT . Using the results of that problem,

b1=1.2409 and Sb1=0.1421

**a.**At the 0.05 level of significance, is there evidence of a

linear relationship between the summated rating of a

restaurant and the cost of a meal?

**b.**Construct a 95% confidence interval estimate of the

population slope, b1.

**12.17** In Problem 12.5 on page 441, you used the summated

rating to predict the cost of a restaurant meal (stored

in )RESTAURANTS ATTACHMENTS. For those data, SSR= 6,951.3963 and SST=15,890.11

**a.**Determine the coefficient of determination, and interpret

its meaning.

**b.**Determine the standard error of the estimate.

**c.**How useful do you think this regression model is for predicting

audited sales?

**10.61**The per-store daily customer count (i.e., the mean number

of customers in a store in one day) for a nationwide convenience

store chain that operates nearly 10,000 stores has been

steady, at 900, for some time. To increase the customer count,

the chain is considering cutting prices for coffee beverages. The

question to be determined is how much to cut prices to increase

the daily customer count without reducing the gross margin on coffee sales too much. You decide to carry out an experiment in a sample of 24 stores where customer counts have been running

almost exactly at the national average of 900. In 6 of the stores, the price of a small coffee will now be $0.59, in 6 stores the price of a small coffee will now be $0.69, in 6 stores, the

price of a small coffee will now be $0.79, and in 6 stores, the price of a small coffee will now be $0.89. After four weeks of selling the coffee at the new price, the daily customer count in

the stores was recorded and stored in COFFEE .

**a.**At the 0.05 level of significance, is there evidence of a

difference in the daily customer count based on the price

of a small coffee?