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 theregression 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 averageambient 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 presentedin the following table:yх1x2x3x42402524911002363121909527045248110274602587883016525919431672269499300802587972968425869626775248811027660259110528850259010026138238998Here is the Excel output from performing the regression analysis:Regression StatisticsMultiple RR SquareAdjusted R Square0.9230654760.852049873Standard Error11.78657744Observations12Coefficients Standard Errort StatP-valueUpper 95% Lower 95.0% Upper 95.0%Lower 95%Intercept-123.1312463157.2560575 -0.78299843x10.7572890890.279089778 2.71342467x27.5187839554.0101214191.8749517x32.4830785551.809385602 1.37233244x4-0.4811352320.55517418 -0.86663834

Given information: The output for multiple linear regression is given.

Answered: The electric power consumed each month…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter3: Functions And Graphs

Section3.3: Lines

Problem 76E

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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 past year’s historical data are available and are presented in the following table: Fit a multiple linear regression model to these data.
A consumer organization wants to develop a regression model to predict gasoline mileage (as measured by miles per gallon) based on the horsepower of the car’s engine and the weight of the car, in pounds. A sample of 50 recent car models was selected, with the results recorded in the file auto.xls. State the multiple regression equation. Interpret the meaning of the slopes, b1 and b2, in this problem. Explain why the regression coefficient, b0, has no practical meaning in the context of this problem. Predict the mean miles per gallon for cars that have 60 horsepower and weigh 2,000 pounds.
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