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## Use the prediction line developed above to predict the price per person for a restaurant with a summed rating of 50

Zagat's publishes restaurant ratings for various locations in the United States. The data file (Zagat) contains the Zagat rating for food, decor, service, and the price per person for a sample of 50 restaurants located in an urban area (NYC) and 50 restaurants located in the NYC suburb. Develop a regression model to predict the price per person, based on the variables. Develop a multiple linear regression model and analyze the results. Develop a CI and PI for two restaurants with Food, Decor and Service with a rating of 20 in each area, but one located in Urban and the other in Suburan.

Assuming you could add all the three indices and ignoting the location, develop a linear relationship, and compute the rehression coefficients b0 and b1.

Interpret the meaning of the Y intercept b0 and the slope b1.

Use the prediction line developed above to predict the price per person for a restaurant with a summed rating of 50.

Compute the coefficient of determination (R squared) and interpret the meaning.

Find the 95% confidence interval and prediction interval of the price per person for a restaurant with a summed rating of 50.