Question o 30 pts Scenario: A local coffee shop is doing extremely well selling its new flavored hot chocolate. However, they want to see if they should keep it as a seasonal item so they take a random sample of days throughout the year. They record the average temperature of the day to see if they can predict the sales in dollars of the new hot chocolate. The following was their output: Regression Statistics Multiple R 0.7915141 R Square 0.6264946 Adjusted R Square 0.6136151 Standard Error 1125.4832 Observations 31 ANOVA df 1 Regression Residual Total SS MS F Significance F 61616421.24 61616421.2 48.64279 1.14508E-07 36734659.47 1266712.4 98351080.21 29 30 Intercept temp Coefficients Standar Error Stat 11940.482 1388.578237 8.59907028 144.74802 20.75407621 -6.9744381 P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 1.8E-09 9100.520476 14780.443 9100.52048 14780.4432 1.15E OZ.187.194822-102.301171-187.194872-102.30117 Q1: What is the business problem? Regression Residual Total 1 61616421.24 61616421.2 48.64279 1.14508E-07 29 36734659.47 1266712.4 30 98351080.71 Intercept temp Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 11940.482 1388.578237 8.59907028 1.8E-09 9100.520476 14780.443 9100.52048 1478C -144.74802 20.75407621 -6.9744381 1.15E-07 -187.194872 -102.30117 -187.194872 -102.5 Q1: What is the business problem? Q2: Is this model simple linear regression or multiple linear regression? Why? Q3: What is the value of correlation coefficient? Interpret it. Q4: How much variation in the sales can be accounted for by temperature? Q5: Write the regression equation based on the output. Q6: What is the slope of the regression equation? Interpret it. Q7: Is the regression model significant at 5%? Why or why not? Q8: What is the business implication of the result? (Less than 50 words) HTML Editora !! IL Question o 30 pts Scenario: A local coffee shop is doing extremely well selling its new flavored hot chocolate. However, they want to see if they should keep it as a seasonal item so they take a random sample of days throughout the year. They record the average temperature of the day to see if they can predict the sales in dollars of the new hot chocolate. The following was their output: Regression Statistics Multiple R 0.7915141 R Square 0.6264946 Adjusted R Square 0.6136151 Standard Error 1125.4832 Observations 31 ANOVA df 1 Regression Residual Total SS MS F Significance F 61616421.24 61616421.2 48.64279 1.14508E-07 36734659.47 1266712.4 98351080.21 29 30 Intercept temp Coefficients Standar Error Stat 11940.482 1388.578237 8.59907028 144.74802 20.75407621 -6.9744381 P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 1.8E-09 9100.520476 14780.443 9100.52048 14780.4432 1.15E OZ.187.194822-102.301171-187.194872-102.30117 Q1: What is the business problem? Regression Residual Total 1 61616421.24 61616421.2 48.64279 1.14508E-07 29 36734659.47 1266712.4 30 98351080.71 Intercept temp Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 11940.482 1388.578237 8.59907028 1.8E-09 9100.520476 14780.443 9100.52048 1478C -144.74802 20.75407621 -6.9744381 1.15E-07 -187.194872 -102.30117 -187.194872 -102.5 Q1: What is the business problem? Q2: Is this model simple linear regression or multiple linear regression? Why? Q3: What is the value of correlation coefficient? Interpret it. Q4: How much variation in the sales can be accounted for by temperature? Q5: Write the regression equation based on the output. Q6: What is the slope of the regression equation? Interpret it. Q7: Is the regression model significant at 5%? Why or why not? Q8: What is the business implication of the result? (Less than 50 words) HTML Editora !! IL
