Homework Answers
Based on the given data the fitted linear regression equation of y on x1 and x2 is
Y=43082.4 + 982.9*x1 + 121.8*x2
Y is the regressed or predicted value of y
so SSR =
= 462318820
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x2 (number pubs) y salary of prof 18 x1 years 51876 54511 2 53425 61863 52926...
Consider the following data for a dependent variable y and two independent variables, x1 and x2...
Consider the following data for a dependent variable y and two independent variables, x1 and x2 . x1 x2 y 30 12 95 46 11 108 24 17 113 50 16 178 41 6 95 51 19 176 75 7 170 37 12 117 60 14 142 77 17 212 Round your all answers to two decimal places. Enter negative values as negative numbers, if necessary. a. Develop an estimated regression equation relating y to x1. y^ = ___ +...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the var...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: 0.04 + 0.28X1 + 0.84X2-0.06x3 + 0.14x4 y She would like to conduct significance tests for a multiple regression relationship. She uses the F test to determine whether a significant relationship exists...
The table shows distance of ball throw (y), grip (x1), stature (x2) and weight (x3) about...
The table shows distance of ball throw (y), grip (x1), stature (x2) and weight (x3) about fifteen boys Derive a multiple regression formula and its multiple correlation coefficient about objective variable that is distance of ball throw (y) Furthermore, derive distance of 10 ball y [m] about a x1-45[kg], x2=158[cm] and x3=60[kg] by using the multiple regression formula Stature Weight| Grip boll throw y[m] x1[kg]x2cm] x3[kg] Distance of 34 22 28 146 36 57 46 169 24 39 25 160...
The table shows distance of ball throw (y), grip (x1), stature (x2) and weight (x3) about...
The table shows distance of ball throw (y), grip (x1), stature (x2) and weight (x3) about fifteen boys Derive a multiple regression formula and its multiple correlation coefficient about objective variable that is distance of ball throw (y) Furthermore, derive distance of 10 ball y [m] about a x1-45[kg], x2=158[cm] and x3=60[kg] by using the multiple regression formula Stature Weight| Grip boll throw y[m] x1[kg]x2cm] x3[kg] Distance of 34 22 28 146 36 57 46 169 24 39 25 160...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the follow...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: y0.35 0.58x1 + 0.45x2-0.25x3 - 0.10x4 He would like to conduct significance tests for a multiple regression relationship. He uses the F test to determine whether a significant relationship exists between the dependent variable and He uses the t...
O. Let X1 and X2 be two random variables, and let Y = (X1 + X2)2....
O. Let X1 and X2 be two random variables, and let Y = (X1 +
X2)2. Suppose that E[Y ] = 25 and that the variance of X1 and X2
are 9 and 16, respectively.
O. Let Xi and X2 be two random variables, and let Y = (X1 X2)2. Suppose that and that the variance of X1 and X2 are 9 and 16, respectively E[Y] = 25 (63) Suppose that both X\ and X2 have mean zero. Then the...
Consider the following data for a dependent variable y and two independent variables, x1 and x2....
Consider the following data for a dependent variable y and two independent variables, x1 and x2. x1 x2 y 30 12 94 47 10 108 25 17 112 51 16 178 40 5 94 51 19 175 74 7 170 36 12 117 59 13 142 76 16 211 The estimated regression equation for the data is ŷ = −18.4 + 2.01x1 + 4.74x2. (a) Develop a 95% confidence interval for the mean value of y when x1 = 65...
Consider the following data for a dependent variable y and two independent variables, x1 and x2....
Consider the following data for a dependent variable y and two independent variables, x1 and x2. x1 x2 y 29 13 94 46 10 109 24 17 112 50 17 178 40 6 94 52 19 176 75 8 171 36 13 118 60 13 143 76 17 212 Round your all answers to two decimal places. Enter negative values as negative numbers, if necessary. a. Develop an estimated regression equation relating y to x1 . y = __ +...
Section C (20 Marks) C1 :Below you are given a partial ISD1: 10 marks] computer output based on a sample of 40 observations. Coefficient Standard Error Constant 25.848 8.85 7.364 K 90.432 5.26 X2...
Section C (20 Marks) C1 :Below you are given a partial ISD1: 10 marks] computer output based on a sample of 40 observations. Coefficient Standard Error Constant 25.848 8.85 7.364 K 90.432 5.26 X2 25.12 Analysis of Varianee Sum of Mean Source of Degrees s Square Variation Regression Error of Freedom Squares 4,853 970.6 1. Use the output shown above and write the estimated regression equation. (2 marks) Interpret the meaning of the coefficient of X1 and X2. (2 marks)...
Given are five observations for two variables, x and y. 4 8 12 16 18 yi...
Given are five observations for two variables, x and y. 4 8 12 16 18 yi 58 51 48 14 15 The estimated regression equation for these data is y= 76.77 - 3.41x a. Compute SSE, SST, and SSR (to 2 SSE decimals) (to 2 SST decimals) (to 2 SSR decimals) b. Compute the coefficient of determination r. Comment on the goodness of fit (to 3 decimals) % of the variability in y has been explained by the estimated regression...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: 0.04 + 0.28X1 + 0.84X2-0.06x3 + 0.14x4 y She would like to conduct significance tests for a multiple regression relationship. She uses the F test to determine whether a significant relationship exists...
The table shows distance of ball throw (y), grip (x1), stature (x2) and weight (x3) about fifteen boys Derive a multiple regression formula and its multiple correlation coefficient about objective variable that is distance of ball throw (y) Furthermore, derive distance of 10 ball y [m] about a x1-45[kg], x2=158[cm] and x3=60[kg] by using the multiple regression formula Stature Weight| Grip boll throw y[m] x1[kg]x2cm] x3[kg] Distance of 34 22 28 146 36 57 46 169 24 39 25 160...
The table shows distance of ball throw (y), grip (x1), stature (x2) and weight (x3) about fifteen boys Derive a multiple regression formula and its multiple correlation coefficient about objective variable that is distance of ball throw (y) Furthermore, derive distance of 10 ball y [m] about a x1-45[kg], x2=158[cm] and x3=60[kg] by using the multiple regression formula Stature Weight| Grip boll throw y[m] x1[kg]x2cm] x3[kg] Distance of 34 22 28 146 36 57 46 169 24 39 25 160...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: y0.35 0.58x1 + 0.45x2-0.25x3 - 0.10x4 He would like to conduct significance tests for a multiple regression relationship. He uses the F test to determine whether a significant relationship exists between the dependent variable and He uses the t...
O. Let X1 and X2 be two random variables, and let Y = (X1 +
X2)2. Suppose that E[Y ] = 25 and that the variance of X1 and X2
are 9 and 16, respectively.
O. Let Xi and X2 be two random variables, and let Y = (X1 X2)2. Suppose that and that the variance of X1 and X2 are 9 and 16, respectively E[Y] = 25 (63) Suppose that both X\ and X2 have mean zero. Then the...
Section C (20 Marks) C1 :Below you are given a partial ISD1: 10 marks] computer output based on a sample of 40 observations. Coefficient Standard Error Constant 25.848 8.85 7.364 K 90.432 5.26 X2 25.12 Analysis of Varianee Sum of Mean Source of Degrees s Square Variation Regression Error of Freedom Squares 4,853 970.6 1. Use the output shown above and write the estimated regression equation. (2 marks) Interpret the meaning of the coefficient of X1 and X2. (2 marks)...
Given are five observations for two variables, x and y. 4 8 12 16 18 yi 58 51 48 14 15 The estimated regression equation for these data is y= 76.77 - 3.41x a. Compute SSE, SST, and SSR (to 2 SSE decimals) (to 2 SST decimals) (to 2 SSR decimals) b. Compute the coefficient of determination r. Comment on the goodness of fit (to 3 decimals) % of the variability in y has been explained by the estimated regression...
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