Below are the input and results of an OLS linear regression. The Q president of a specialty fruit juice company believed that for every single degree change in average temperature during the summer months, the profit would decline 3%. This informa¬tion was used to prepare budgets. The president obtained forecasts of the average summer temperature then requested the budget be adjusted. The table of values presents the raw data for temperatures (Predictor Variable X) and net income (Outcome Variable Y).

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kegression Statistics Degrees C 0.017029265 19 18 $943.84316 $47.12590 Std Error t-Stat P-value R Square Observations df Intercepta Slope b Confidence Critical value of df= 18 2440.03187 0.386816 0.70369 0.54269 0.9439 86.8375498 95.00% 95.00% 2.101 2.101 Profit y, OLS Linear Regression Line 5,000 $4,000 t-4-Predicted Y!' .. $3,000 $2,000 1,000 $0 30 40 20 X = Degrees C 68 3 5 2 0 0 9 0 2 7 4 7 2 2 0 0 55 0060067 5 7 3 4 3 1 7 3 1 413582824 1.1 1 1 1 2 1 2 2 2 2 3 3 3 4 1 2 2 .6 3 5 1 3 0 1 9 0 3 1 8 2 659521 2458910618991847689 R I-2222233232223222222 0 345678901234 5678901 321 2 0 1111111222222222222 slenp-say a