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2. Multivariate Regression. Now add to your above regression in a price variable, wit 8, 7.5, 7.25, 7.25, 6, 6.75, 6, 5, 4.4, 5.2. Estimate the new regression equation. Print re results. Write out the estimated demand function, as in 1 above. Equation: Std Errors R² =

2. Multivariate Regression. Now add to your above regression in a price variable, wit 8, 7.5, 7.25, 7.25, 6, 6.75, 6, 5, 4.4, 5.2. Estimate the new regression equation. Print re results. Write out the estimated demand function, as in 1 above. Equation: Std Errors R² =

MATLAB: An Introduction with Applications
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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question one is answered need help with #2

Consider the following data Sales Adv Y₁ X₁ mtontonage INSoroad 3 4 6 5 7 6 5 9 10 9 1 2 3 4 5 6 7 8 9 10 1. Input this data on a spreadsheet. Using the regression option, generate regression predictions. Write your results as an equation, as we did in class. In particular, (a) Write the regression equation, with estimated coefficients, (b) Below the regression equation, list in parentheses the standard errors of the coefficient estimates (c) To the right of the estimated equation write R² = . Equation: Yi=2.734 + .667Xi R² = .7575 Std Errors: (0.827) (0.134)
Transcribed Image Text:Consider the following data Sales Adv Y₁ X₁ mtontonage INSoroad 3 4 6 5 7 6 5 9 10 9 1 2 3 4 5 6 7 8 9 10 1. Input this data on a spreadsheet. Using the regression option, generate regression predictions. Write your results as an equation, as we did in class. In particular, (a) Write the regression equation, with estimated coefficients, (b) Below the regression equation, list in parentheses the standard errors of the coefficient estimates (c) To the right of the estimated equation write R² = . Equation: Yi=2.734 + .667Xi R² = .7575 Std Errors: (0.827) (0.134)
2. Multivariate Regression. Now add to your above regression in a price variable, with values: 8, 7.5, 7.25, 7.25, 6, 6.75, 6, 5, 4.4, 5.2. Estimate the new regression equation. Print regression results. Write out the estimated demand function, as in 1 above. Equation: Std Errors R² =
Transcribed Image Text:2. Multivariate Regression. Now add to your above regression in a price variable, with values: 8, 7.5, 7.25, 7.25, 6, 6.75, 6, 5, 4.4, 5.2. Estimate the new regression equation. Print regression results. Write out the estimated demand function, as in 1 above. Equation: Std Errors R² =
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