How do you interpret the quality of this causal forecast

Question

Problem

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 [^oF]     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

1) How much demand can the store expect if the temperature is 72^oF?
2) How do you interpret the b coefficient in this linear regression equation?
3) How do you interpret the quality of this causal forecast?