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of A uncw.instructure.com Bob's Burgers is a chain of hamburger fast food restaurants located all over the state of Alaska. Bob, the OM, has collected sales data from their famous Jalapeño Burger over the past 5 weeks, and wants to generate a linear regression equation to estimate potential sales for upcoming weeks. Given the data below, what is the regression equation? Jalapeño Burger Week Sales 354 345 367 3. 380 4. 413 5. Use the Summary Output below to write the equation for the model that explains the linear relationship between weeks and Jalapeño Burger sales? SUMMARY OUTPUT Regression Statistics Multiple R 0.91065 R Square 0.829283 Adjusted R 0.772377 Square Standard 12.67412 Error Observations 5 ANOVA Significance SS MS F. Regression 1. 2340.9 2340.9 14.57294 0.031628 Residual 481.9 160.6333 3. uncw.instructure.com 413 5. Use the Summary Output below to write the equation for the model that explains the linear relationship between weeks and Jalapeño Burger sales? SUMMARY OUTPUT Regression Statistics Multiple R 0.91065 R Square 0.829283 Adjusted R Square 0.772377 Standard 12.67412 Error Observations 5 ANOVA Significance df SS MS Regression 2340.9 6'0 14.57294 0.031628 1. Residual 481.9 160.6333 3. Total 2822.8 4. Standard Upper Lower Upper Coefficients t Stat P-value Lower 95% Error 95% Intercept 325.9 13.29273 24.51716 0.000149 283.5966 368.2034 283.5966 368.2034 X Variable 15.3 4.007909 3.817452 0.031628 2.545045 2805495 2.545045 28.05495 O Y(X) = 325.9X + 15.3 O Y(X) = 15.3X + 325.9 %3D No regression equation can be obtained from the data provided. MacBook Air

of A uncw.instructure.com Bob's Burgers is a chain of hamburger fast food restaurants located all over the state of Alaska. Bob, the OM, has collected sales data from their famous Jalapeño Burger over the past 5 weeks, and wants to generate a linear regression equation to estimate potential sales for upcoming weeks. Given the data below, what is the regression equation? Jalapeño Burger Week Sales 354 345 367 3. 380 4. 413 5. Use the Summary Output below to write the equation for the model that explains the linear relationship between weeks and Jalapeño Burger sales? SUMMARY OUTPUT Regression Statistics Multiple R 0.91065 R Square 0.829283 Adjusted R 0.772377 Square Standard 12.67412 Error Observations 5 ANOVA Significance SS MS F. Regression 1. 2340.9 2340.9 14.57294 0.031628 Residual 481.9 160.6333 3. uncw.instructure.com 413 5. Use the Summary Output below to write the equation for the model that explains the linear relationship between weeks and Jalapeño Burger sales? SUMMARY OUTPUT Regression Statistics Multiple R 0.91065 R Square 0.829283 Adjusted R Square 0.772377 Standard 12.67412 Error Observations 5 ANOVA Significance df SS MS Regression 2340.9 6'0 14.57294 0.031628 1. Residual 481.9 160.6333 3. Total 2822.8 4. Standard Upper Lower Upper Coefficients t Stat P-value Lower 95% Error 95% Intercept 325.9 13.29273 24.51716 0.000149 283.5966 368.2034 283.5966 368.2034 X Variable 15.3 4.007909 3.817452 0.031628 2.545045 2805495 2.545045 28.05495 O Y(X) = 325.9X + 15.3 O Y(X) = 15.3X + 325.9 %3D No regression equation can be obtained from the data provided. MacBook Air

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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of A uncw.instructure.com Bob's Burgers is a chain of hamburger fast food restaurants located all over the state of Alaska. Bob, the OM, has collected sales data from their famous Jalapeño Burger over the past 5 weeks, and wants to generate a linear regression equation to estimate potential sales for upcoming weeks. Given the data below, what is the regression equation? Jalapeño Burger Week Sales 354 345 367 3. 380 4. 413 5. Use the Summary Output below to write the equation for the model that explains the linear relationship between weeks and Jalapeño Burger sales? SUMMARY OUTPUT Regression Statistics Multiple R 0.91065 R Square 0.829283 Adjusted R 0.772377 Square Standard 12.67412 Error Observations 5 ANOVA Significance SS MS F. Regression 1. 2340.9 2340.9 14.57294 0.031628 Residual 481.9 160.6333 3.
Transcribed Image Text:of A uncw.instructure.com Bob's Burgers is a chain of hamburger fast food restaurants located all over the state of Alaska. Bob, the OM, has collected sales data from their famous Jalapeño Burger over the past 5 weeks, and wants to generate a linear regression equation to estimate potential sales for upcoming weeks. Given the data below, what is the regression equation? Jalapeño Burger Week Sales 354 345 367 3. 380 4. 413 5. Use the Summary Output below to write the equation for the model that explains the linear relationship between weeks and Jalapeño Burger sales? SUMMARY OUTPUT Regression Statistics Multiple R 0.91065 R Square 0.829283 Adjusted R 0.772377 Square Standard 12.67412 Error Observations 5 ANOVA Significance SS MS F. Regression 1. 2340.9 2340.9 14.57294 0.031628 Residual 481.9 160.6333 3.
uncw.instructure.com 413 5. Use the Summary Output below to write the equation for the model that explains the linear relationship between weeks and Jalapeño Burger sales? SUMMARY OUTPUT Regression Statistics Multiple R 0.91065 R Square 0.829283 Adjusted R Square 0.772377 Standard 12.67412 Error Observations 5 ANOVA Significance df SS MS Regression 2340.9 6'0 14.57294 0.031628 1. Residual 481.9 160.6333 3. Total 2822.8 4. Standard Upper Lower Upper Coefficients t Stat P-value Lower 95% Error 95% Intercept 325.9 13.29273 24.51716 0.000149 283.5966 368.2034 283.5966 368.2034 X Variable 15.3 4.007909 3.817452 0.031628 2.545045 2805495 2.545045 28.05495 O Y(X) = 325.9X + 15.3 O Y(X) = 15.3X + 325.9 %3D No regression equation can be obtained from the data provided. MacBook Air
Transcribed Image Text:uncw.instructure.com 413 5. Use the Summary Output below to write the equation for the model that explains the linear relationship between weeks and Jalapeño Burger sales? SUMMARY OUTPUT Regression Statistics Multiple R 0.91065 R Square 0.829283 Adjusted R Square 0.772377 Standard 12.67412 Error Observations 5 ANOVA Significance df SS MS Regression 2340.9 6'0 14.57294 0.031628 1. Residual 481.9 160.6333 3. Total 2822.8 4. Standard Upper Lower Upper Coefficients t Stat P-value Lower 95% Error 95% Intercept 325.9 13.29273 24.51716 0.000149 283.5966 368.2034 283.5966 368.2034 X Variable 15.3 4.007909 3.817452 0.031628 2.545045 2805495 2.545045 28.05495 O Y(X) = 325.9X + 15.3 O Y(X) = 15.3X + 325.9 %3D No regression equation can be obtained from the data provided. MacBook Air
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