Fit a multiple linear regression model to the given data. as X1,X2,X5, and X6 as regressors. y8.08.38.58.89.09.39.39.59.810.010.310.510.811.011.311.511.812.312.5X119.619.819.619.418.618.820.419.020.819.918.020.620.220.219.217.019.818.818.6x₂94.989.796.295.686.584.588.885.793.686.087.193.183.494.583.485.284.186.983.0X32.31.82.02.11.82.11.91.92.11.81.62.12.11.91.82.11.81.82.0X₂5.25.25.86.45.85.25.66.05.25.86.46.06.26.26.25.66.05.85.6X529.632.431.032.428.630.632.432.632.231.832.633.431.832.431.433.235.434.034.2X62.12.12.02.22.02.12.22.12.32.12.02.12.22.11.92.12.02.11.9NN

Procedure to find multiple linear regression using Excel: Enter the data of y, X1, X2, X5, and X6…

Answered: Fit a multiple linear regression model…

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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Explain the concept of Linear Regression with Multiple Regressors?
Suppose that in R we have loaded the cps dataset, which contains the variables wage, educ, and exper. We want to run a regression of wage on edục and exper and save the output in a variable called regout. What is the correct command for this operation? O a. regout = 1m(wage = educ + exper, data = cps) O b. 1m(wage educ + exper, data = cps) 1m(wage educ + exper, data = cps) O e. regout <- lm(wage - educ + exper, data = cps) Clear my choice
The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A and Company B for 10 years. The equation of the regression line is y = 0.991x + 1,222.81. Complete parts (a) and (b) below. D New-vehicle sales (Company A), x New-vehicle sales (Company B), y 4,149 3,923 3,566 3,400 3,266 3,076 2,868 2,485 1,952 2,066 4,912 4,871 4,827 4,721 4,672 4,474 4,684 3,822 2,956 2,754 (a) Find the coefficient of determination and interpret the result. 12²=0 (Round to three decimal places as needed.) 1
(please solve within 15 minutes I will give thumbs up)
An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If the advertising budgets of one of the branches of the corporation is now $45,000 (which is 10% more than before) and the salary of sales representatives is now $8,500 (which is 20% less than before), then the predicted sales will a. increase by more than 10% b. increase by less than 10% c. decrease by less than 10% d. be the same
Which of the following is true of a linear regression line? a. Located as close as possible to all the points of a scatter chart. B. Is defined by an equation having 2 parameters: the slope and the intercept c. Provides an approximate relationship between the values of two parameters d. All of the above
Write out the full linear model including all dummy variables below. Don’t worry about estimating regression coefficients just yet. Feel free to abbreviate variable names so long as they are clearly distinguishable.
Fit the following points, (17,8), (18,10), (23,6), (24,5), (27,5), and (32,2). Predict the f(28). A. second-order polynomial Regression B. Simple Linear Regression
You are the Filipino analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. You used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2 If the advertising budgets of one of the branches of the corporation is the same as before and the salary of sales representatives is now 20% less than before, then the predicted sales in that branch will A. increase B. no sufficient information to determine C. decrease D. remain the same

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