Recall that R² is the multiple coefficient of determination and is an indication of the goodness of fit for an estimated multiple regression equation. That is, it is the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation. Since it is a proportion, it will only take on values between 0 and 1. It is calculated as follows where SSR is the sum of squares due to regression and SST is the total sum of squares. SSR R2 = SST We are given that SST = 1,808 and SSR = 1,778. Use these values to find the value of R2, rounding the result to three decimal places. SSR R2 SST 1,778

Recall that R² is the multiple coefficient of determination and is an indication of the goodness of fit for an estimated multiple regression equation. That is, it is the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation. Since it is a proportion, it will only take on values between 0 and 1. It is calculated as follows where SSR is the sum of squares due to regression and SST is the total sum of squares. SSR R2 = SST We are given that SST = 1,808 and SSR = 1,778. Use these values to find the value of R2, rounding the result to three decimal places. SSR R2 SST 1,778

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x,) and newspaper advertising (x,). The estimated regression equation was ý = 83.3 + 2.24x, + 1.30x2. The computer solution, based on a sample of eight weeks, provided SST 25.2 and SSR = 23.455. %D (a) Compute and interpret R² and R,. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is . Adjusting for the number of independent variables in the model, the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is (b) When television advertising was the only independent variable, R = 0.653 and R, = 0.595. Do you prefer the multiple regression results? Explain. %3D 2 Multiple regression analysi v ---Select--- ipreferred since both R2 and R, show ---Select--- O…
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