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Regression analysis

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The file attached contains data on 80 colleges and universities. Among the variables included are the academic calendar type (1 = semester: 0 = other). Annual total cost (in thousands of dollars), average total score on the Scholastic Aptitude Test (SAT), room and board expenses (in thousands of dollars), whether the institution is public or private, whether the TOEFL criterion is at least 550, and average indebtedness at graduation. Develop the most appropriate multiple regression model to predict average indebtedness at graduation.
Be sure to perform a thorough residual analysis. In addition, provide a detailed explanation of your results, using Microsoft Excel:

1- State the sample multiple regression equation.
2- Interpret the meaning of the slopes in this problem.
3- Perform a residual analysis on your results and determine the adequacy of the fit of the model.
4- At the .05 level of significance, determine whether each explanatory variable makes a contribution to the regression model.
5- On the basis of these results, indicate the regression model that should be used in this problem.
6- Interpret the meaning of the coefficient of multiple determination R2
7- Include an interaction term in the model and at the .05 level of significance determine whether it makes a significant contribution to the model.

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

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