**Exhibit 15-33**In a regression model involving 44 observations, the following estimated regression equation was obtained:\[\hat{y} = 10 - 4x_1 - 2x_2 + 8x_3 + 8x_4\]For this model, SSR (Sum of Squares for Regression) = 500 and SSE (Sum of Squares for Error) = 3500.Refer to Exhibit 15-33. The coefficient of determination for the above model is approximately ______.- ○ –.875- ○ .144- ● .125- ○ .875*Note:* The coefficient of determination (R²) is calculated using the formula:\[R^2 = \frac{SSR}{SSR + SSE}\]

Given,SSR=500and SSE=3500SST=SSE+SSRSST=500+3500SST=4000Coefficient of determination=SSRSSTCoefficient of determination=5004000Coefficient of determination=18Coefficient of determination=0.125The Coefficient of determination for the given modelis 0.125 .

Math

Statistics

In a regression model involving 44 observations, the following estimated regression equation was obtained: ŷ= 10 - 4x12x2 + 8x3 + 8x4 For this model, SSR = 500 and SSE = 3500. Refer to Exhibit 15-33. The coefficient of determination for the above model is approximately -.875 .144 .125 .875

In a regression model involving 44 observations, the following estimated regression equation was obtained: ŷ= 10 - 4x12x2 + 8x3 + 8x4 For this model, SSR = 500 and SSE = 3500. Refer to Exhibit 15-33. The coefficient of determination for the above model is approximately -.875 .144 .125 .875

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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