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

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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.