Regression using Energy Drink Data
HW#3
Run regression analysis using the Energy Drinks Data posted on elearning. You can work by yourself, or work in a group (up to 5 students per group) and submit one homework per group.
1. (a) Run the linear regression model that express quantity sales (oz) of Full-Throttle as the dependent variable; the list of explanatory variables are price of Full-Throttle, the price of Monster, price of Red Bull, price of Rockstar and customer count. Submit the excel output. What is the R2 value? What does the R2 value tell us?
R2 = 45.5%;
45.5% of the variation in the dependent variable explained by the regression equation.
(b) Using the regression results, predict the quantity sales (oz) of Full-Throttle when price of Full-Throttle is $0.08/oz, price of Monster is $0.12/oz, price of Red Bull is $0.20/oz, price of Rockstar is $0.10/oz and customer count is 32000.
(-2458.48) + (-39549.70) * 0.08 + 0.12 * 19739.74 + 0.20 * 7159.01 + 0.10 * 18365.31 + 0.082 * 32000 = 2638.646
(c). Given the prices and customer count number from question 2, calculate the own price elasticity of Full-Throttle. Should the manager increase or decrease the price of Full-Throttle if he wants to increase the revenue from Full-Throttle.
(-39549.7) * 0.08/2638.65 = -1.2;
Decrease the price of Full-Throttle to increase the revenue.
(D). Given the prices and customer count number from question 2, calculate the cross price elasticity between Full-throttle and Rockstar. Are they substitutes? What is the change in the sales of Full-Throttle if the price of Rockstar decreases by 15%?
Cross elasticity = 18365.31 * 0.1/2638.65 = 0.70;
They are substitutes;
-15% * 0.70 = -10.50% (decrease by 10.5%).
2. Use OLS method to analyze quantity sales (oz) of Full-Throttle ( as the multiplicative function of price of Full-Throttle (), price of Monster (), price of Red Bull (), price of Rockstar ()and customer count (. The logarithmic (multiplicative) model is given as follows:
Run regression analysis using the Energy Drinks Data posted on elearning. You can work by yourself, or work in a group (up to 5 students per group) and submit one homework per group.
1. (a) Run the linear regression model that express quantity sales (oz) of Full-Throttle as the dependent variable; the list of explanatory variables are price of Full-Throttle, the price of Monster, price of Red Bull, price of Rockstar and customer count. Submit the excel output. What is the R2 value? What does the R2 value tell us?
R2 = 45.5%;
45.5% of the variation in the dependent variable explained by the regression equation.
(b) Using the regression results, predict the quantity sales (oz) of Full-Throttle when price of Full-Throttle is $0.08/oz, price of Monster is $0.12/oz, price of Red Bull is $0.20/oz, price of Rockstar is $0.10/oz and customer count is 32000.
(-2458.48) + (-39549.70) * 0.08 + 0.12 * 19739.74 + 0.20 * 7159.01 + 0.10 * 18365.31 + 0.082 * 32000 = 2638.646
(c). Given the prices and customer count number from question 2, calculate the own price elasticity of Full-Throttle. Should the manager increase or decrease the price of Full-Throttle if he wants to increase the revenue from Full-Throttle.
(-39549.7) * 0.08/2638.65 = -1.2;
Decrease the price of Full-Throttle to increase the revenue.
(D). Given the prices and customer count number from question 2, calculate the cross price elasticity between Full-throttle and Rockstar. Are they substitutes? What is the change in the sales of Full-Throttle if the price of Rockstar decreases by 15%?
Cross elasticity = 18365.31 * 0.1/2638.65 = 0.70;
They are substitutes;
-15% * 0.70 = -10.50% (decrease by 10.5%).
2. Use OLS method to analyze quantity sales (oz) of Full-Throttle ( as the multiplicative function of price of Full-Throttle (), price of Monster (), price of Red Bull (), price of Rockstar ()and customer count (. The logarithmic (multiplicative) model is given as follows: