A Home Depot store in Jacksonville wants to forecast the demand of fire pits during the first winter weekends. The product manager found that in the past there has been a link between temperature and  sales of fire pits. She wants to build a causal forecast model with the following data collected over the past winter.

 

Temperature [°F]             Daily sales (Unit)
62                                        40

65                                        32 
71                                         23 
76                                        12 
78                                         6 
81                                          7 
86                                         5 
88                                         4 
91                                          1 

 

Y = -1.3068x + 115.79
R² = 0.9036

 

Required:
a. How much demand can the store expect if the temperature is 72°F? 
b. How do you interpret the b coefficient in this linear regression equation? 
c. How do you interpret the quality of this causal forecast? 

Answer rating: 100% (QA)

a To determine the expected demand if the temperature is 72F we can plug in the value of 72F into th... View the full answer