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    Regression analysis of real estate data

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    Refer to the data included in the Excel file, which report information on homes sold in the Somewhere, USA, during a recent year. Use the selling price of the home as the dependent variable and determine the regression equation with number of bedrooms, size of the house, whether there is a pool, whether there is an attached garage, distance from the center of the
    city, and the number of bathrooms as independent variables.

    i) Construct a 95% confidence interval estimate of the population slope between selling price and each of the following variables: number of bedrooms, size in sq. ft., distance to CBD, and number of bathrooms.
    j) Compute and interpret the coefficients of partial determination.
    k) Predict the selling price of a 2,500 square feet house that has 5 bedrooms, 3 bathrooms,
    a 3-car attached garage, no pool, and is at 18 miles from the city center.
    l) Rerun the analysis until only significant regression coefficients remain in the analysis. Identify these variables.

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    https://brainmass.com/statistics/regression-analysis/regression-analysis-of-real-estate-data-248352

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    Solution Summary

    The solution provides step by step method for the calculation of regression model . Formula for the calculation and Interpretations of the results are also included.

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