A pool supplies store found that the demand for chlorine increases as water temperature in pools  increases. The store collected historical data on this causal relationship and found the following linear  regression equation: y = 3.4729x - 154.41.   The R^2 is 0.96. Demand is expressed in lbs. and temperature in °F. 

a. The expected water temperature next week will be 75°F. How much demand of chlorine should the store forecast? 

b. Last week, the water temperature was 70°F and the demand of chlorine was 105 lbs. How much was the forecast error (i.e., difference between actual demand and forecast)? 

c. EXTRA QUESTION - NOT PART OF EXAM MATERIAL: Please use Excel and the data in the table below to find the linear regression equation of this problem?

 

Water temperature [°F]                Daily demand for chlorine [lbs.] 

48                                                    25 
54                                                    34 
58                                                    39 
62                                                    53 
65                                                    73 
68                                                    82 
72                                                    96 
78                                                    105 
79                                                    112 
81                                                     124 
84                                                    148 
86                                                    156