16. Given are five observations for two variables, x and y. Given are five observations for two variables, x and y.49 121420Yi5052402210The estimated regression equation for these data is ŷ = 68.09 – 2.82x,a. Compute SSE, SST, and SSR.SSE(to 2 decimals)SST(to 2 decimals)SSR(to 2 decimals)b. Compute the coefficient of determination r. Comment on the goodness of fit.(to 3 decimals)The least squares line provided anSelect your answer -v fit;% of the variability in y has been explained by the estimated regression equation (to 1decimal).c. Compute the sample correlation coefficient. Enter negative value as negative number.(to 3 decimals)

In regression analysis, by using the terms SSE, SST and SSR we have the following formulae…

Answered: Given are five observations for two…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Given are five observations for two variables, x and y. x 1 2 3 4 5 y 4 7 7 11 13 Develop the estimated regression equation by computing the values of b0 and b1 (to 1 decimals).y=___________ + ___________xUse the estimated regression equation to predict the value of y when x=3 (to 1 decimals). y=___________
Given are five observations for two variables, x and y.x 3 12 6 20 14y 65 50 65 15 18a. Develop a scatter diagram for these data.b. Compute correlation between x and y variable.c. Develop the estimated regression equation by computing b0 and b1
Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 4 6 6 11 13 Develop the estimated regression equation by computing the values of b0 and b1 using b1 = Σ(xi − x)(yi − y) Σ(xi − x)2 and b0 = y − b1x. ŷ = (e) Use the estimated regression equation to predict the value of y when x = 2.
Given are five observations for two variables, x and y.x 3 12 6 20 14y 65 50 65 15 18a. Develop a scatter diagram for these data.b. Compute correlation between x and y variable.c. Develop the estimated regression equation by computing b0 and b
4.For a sample of 12 observations, a businessman wants to regress the price (in dollar) of the laptop (Y) on the processor's speed (X). The summary results of the observations are given below. Σx = 19.8 , Σy = 24798, Σxy = 431882 Σx^2 = 33.88, Σγ^2 = 57365692 (b)Find the fitted regression line of the price of laptop on processor speed. (c) Find the predicted price of the laptop (y) for the processor speed x-1.9. (d) Compute the coefficient of determination and comment.
Consider the following data for two variables, x and y. x 22 24 26 30 35 40 y 11 21 34 36 39 36 Develop an estimated regression equation for the data of the form ŷ = b0 + b1x + b2x2. (Round b0 to one decimal place and b1 to two decimal places and b2 to four decimal places.) ŷ = (e) Use the results from part (d) to test for a significant relationship between x, x2, and y. Use ? = 0.05. Is the relationship between x, x2, and y significant? Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value = (f) Use the model from part (d) to predict the value of y when x = 25. (Round your answer to three decimal places.)
Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 4 6 5 9 14 Develop the estimated regression equation by computing the the slope and the y intercept of the estimated regression line (to 1 decimal). y^= + x Use the estimated regression equation to predict the value of y when x = 5 (to 1 decimal).y^ =
Given are five observations for two variables, x and y. xi 3 12 6 20 14 yi 55 45 50 15 20 #1) Develop the estimated regression equation by computing the values of b0 and b1 using b1 = Σ(xi − x)(yi − y) Σ(xi − x)2 and b0 = y − b1x. y= #2) Use the estimated regression equation to predict the value of y when x = 13.
The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 The values of SST and SSR are 1,808 and 1,780, respectively. (a) Compute R2. (b) Compute Ra2. (c) Comment on the goodness of fit.
The following estimated regression equation based on 10 observations was presented. ŷ = 29.1260 + 0.5306x1 + 0.4680x2 The values of SST and SSR are 6,728.125 and 6,215.375, respectively. (a) Find SSE. SSE = (b) Compute R2. (Round your answer to three decimal places.) R2 = (c) Compute Ra2. (Round your answer to three decimal places.) Ra2 = (d) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation provided a good fit as a large proportion of the variability in y has been explained by the estimated regression equation.
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Given are five observations for two variables, x and y. x 5 11 8 23 18 y 50 47 50 10 23 Develop the estimated regression equation by computing the values of b0 and b1 using equations: (Enter negative values as negative figure) y=___________+___________x (to 2 decimals) Use the estimated regression equation to predict the value of y when x=14. y=______________(to 2 decimals

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