As a class project, students in a large statistics class collected publicly available information on recent home sales in their hometowns There are 894 properties Important predictors of the price of a home are its living area (sq ft) and the number of bathrooms In fact, the correlation of Price with Bathrooms is 0 378 Here is a regression a) What is a correct interpretation of the coefficient of Bathrooms Here is a partial regression plot for the coefficient of Bathrooms along with a least squares regression line b) What is the slope of the regression line in this plot Response variable is Price R squared 16 6 s 263970 Variable Intercept Living area Bathrooms Coefficient 126832 64 6077 75020 3

Question: As a class project, students in a large statistics class collected publicly available information on recent home sales in their hometowns. There are 894 properties.

As a class project, students in a large statistics class collected publicly available information on recent home sales in their hometowns. There are 894 properties. Important predictors of the price of a home are its living area (sq ft) and the number of bathrooms. In fact, the correlation of Price with Bathrooms is 0.378. Here is a regression:

Response variable is: Price R squared = 16.6% s = 263970 Variable

a) What is a correct interpretation of the coefficient of Bathrooms? Here is a partial regression plot for the coefficient of Bathrooms along with a least squares regression line:

Intercept Living area Bathrooms Coefficient 126832 64.6077 75020.3

b) What is the slope of the regression line in this plot?

Response variable is: Price R squared = 16.6% s = 263970 Variable Intercept Living area Bathrooms Coefficient 126832 64.6077 75020.3

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