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The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x1), the number of days in the month (x2), the average product purity (x3), and the tons of product produced (x4). The past year's historical data are available and are presented in the following table:

The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x1), the number of days in the month (x2), the average product purity (x3), and the tons of product produced (x4). The past year's historical data are available and are presented in the following table:

A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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ONLY need for Part D, E, F, Thank you!

(a) Fit the multiple regression model to these data. (b) Interpret the meaning of the slopes bl and b2 in this problem. (c) Predict the electric power consumption with x1 = 62, x2 = 22, x3 = 88 and x4 = 106 (d) At the 0.05 level of significance, determine whether X1 and X2 make a contribution to the regression model respectively. (e) Interpret the meaning of the coefficient of multiple determination. (f) Compute the adjusted r².
Transcribed Image Text:(a) Fit the multiple regression model to these data. (b) Interpret the meaning of the slopes bl and b2 in this problem. (c) Predict the electric power consumption with x1 = 62, x2 = 22, x3 = 88 and x4 = 106 (d) At the 0.05 level of significance, determine whether X1 and X2 make a contribution to the regression model respectively. (e) Interpret the meaning of the coefficient of multiple determination. (f) Compute the adjusted r².
QI) The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x1), the number of days in the month (x2), the average product purity (x3), and the tons of product produced (x4). The past year's historical data are available and are presented in the following table: y х1 x2 x3 x4 240 25 24 91 100 236 31 21 90 95 270 45 24 8 110 274 60 25 87 88 301 65 25 91 94 316 72 26 94 99 300 80 25 87 97 296 84 25 86 96 267 75 24 88 110 276 60 25 91 105 288 50 25 90 100 261 38 23 89 98 Here is the Excel output from performing the regression analysis: Regression Statistics Multiple R R Square Adjusted R Square 0.923065476 0.852049873 Standard Error 11.78657744 Observations 12 Coefficients Standard Error t Stat P-value Upper 95% Lower 95.0% Upper 95.0% Lower 95% Intercept -123.1312463 157.2560575 -0.78299843 x1 0.757289089 0.279089778 2.71342467 x2 7.518783955 4.010121419 1.8749517 x3 2.483078555 1.809385602 1.37233244 x4 -0.481135232 0.55517418 -0.86663834
Transcribed Image Text:QI) The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x1), the number of days in the month (x2), the average product purity (x3), and the tons of product produced (x4). The past year's historical data are available and are presented in the following table: y х1 x2 x3 x4 240 25 24 91 100 236 31 21 90 95 270 45 24 8 110 274 60 25 87 88 301 65 25 91 94 316 72 26 94 99 300 80 25 87 97 296 84 25 86 96 267 75 24 88 110 276 60 25 91 105 288 50 25 90 100 261 38 23 89 98 Here is the Excel output from performing the regression analysis: Regression Statistics Multiple R R Square Adjusted R Square 0.923065476 0.852049873 Standard Error 11.78657744 Observations 12 Coefficients Standard Error t Stat P-value Upper 95% Lower 95.0% Upper 95.0% Lower 95% Intercept -123.1312463 157.2560575 -0.78299843 x1 0.757289089 0.279089778 2.71342467 x2 7.518783955 4.010121419 1.8749517 x3 2.483078555 1.809385602 1.37233244 x4 -0.481135232 0.55517418 -0.86663834
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