For items 3-6, refer to the following software output. The Data Analysis ToolPak in Excel was used to analyze the dataset above. Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Advertising cost (S) 0.634837268 0.403018356 0.343320192 50.2256962 df 12 1 10 11 SS MS F Significance F 17030.04442 17030.04 6.750934 0.026570895 25226.20558 2522.621 42256.25 Coefficients Standard Error t Stat P-value 279.2893401 68.69285999 4.06577 0.002265 3.220812183 1.239605445 2.598256 0.026571 4. Present the simple linear regression model using the following format: Y = bo. b₂x. Interpret the slope of the estimated regression line. 6. Another retail merchant who sells face masks spent a total of $55 for advertising its product. Using the regression model in (4), predict the sales of this merchant.
For items 3-6, refer to the following software output. The Data Analysis ToolPak in Excel was used to analyze the dataset above. Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Advertising cost (S) 0.634837268 0.403018356 0.343320192 50.2256962 df 12 1 10 11 SS MS F Significance F 17030.04442 17030.04 6.750934 0.026570895 25226.20558 2522.621 42256.25 Coefficients Standard Error t Stat P-value 279.2893401 68.69285999 4.06577 0.002265 3.220812183 1.239605445 2.598256 0.026571 4. Present the simple linear regression model using the following format: Y = bo. b₂x. Interpret the slope of the estimated regression line. 6. Another retail merchant who sells face masks spent a total of $55 for advertising its product. Using the regression model in (4), predict the sales of this merchant.
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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