Given are five observations for two variables, z and y.z 3 9 10 18 20| 53 55 50 14 16The estimated regression equation for these data is y 70.38 – 2.73z.a. Compute SSE, SST, and SSR.SSE(to 2 decimals)230(to 2 decimals)(to 2 decimals)b. Compute the coefficient of determination. Comment on the goodness of fit.SSTSSR(to 3 decimals)The least squares line provided an poodexplained by the estimated regression equation (to 1 decimal).c. Compute the sample correlation coefficient. Enter negative value as negative number.% of the variability in y has been(to 3 decimals)

Sample size = n = 5. Follow the steps to perform regression in excel: 1. Select regression from data…

Given are five observations for two variables, a and y. |39 10 18 20 53 55 50 14 16 The estimated regression equation for these data is y- 70.38 - 2.73a. a. Compute SSE, S8T, and SSR. SSE 230 (to a decimals) SST (to 2 decimals) (to a decimals) b. Compute the coeffient of determination . comment on the goodness of fit. SSR O (to a decimals) The least squares line provided an poed explained by the estimated regression equation (to 1 decimal). . Compute the sample correlation coefficient. Enter negative value as negative number. of the variability in y has been (to 3 decimals)

Given are five observations for two variables, a and y. |39 10 18 20 53 55 50 14 16 The estimated regression equation for these data is y- 70.38 - 2.73a. a. Compute SSE, S8T, and SSR. SSE 230 (to a decimals) SST (to 2 decimals) (to a decimals) b. Compute the coeffient of determination . comment on the goodness of fit. SSR O (to a decimals) The least squares line provided an poed explained by the estimated regression equation (to 1 decimal). . Compute the sample correlation coefficient. Enter negative value as negative number. of the variability in y has been (to 3 decimals)

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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Given are five observations for two variables, x and y. Use the estimated regression equation: y = 73.9561 - 3.1463x (NEED ANSWERS FOR A, B, C, D, E)
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