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U m ' Day Peak Load -l Temperature 118.5 136.0 143.6 153.2 140.7 151.9 135.1 178.2 101.6 103.9 113.4 106.2 111.4 116.5 105.1 114.7 131.7

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U m '

Day Peak Load -l Temperature 118.5 136.0 143.6 153.2 140.7 151.9 135.1 178.2 101.6 103.9 113.4 106.2 111.4 116.5 105.1 114.7 131.7 100.9 92.5 132.0 116.4 40. Chapter 10 - Problem 40 A power company located in southern Alabama wants to predict the peak power load (i.e., the maximum amount of power that must be generated each day to meet demand) as a function of the daily high tempera- ture (X). A random sample of summer days is chosen, and the peak power load and the high temperature are recorded each day. The file PIO_40.xIsx contains these observations. a. Create a scatterplot for these data. Comment on the observed relationship between Y and X. b. Estimate an appropriate regression equation to predict the peak power load for this power company. Interpret the estimated regression coefficients. c. Analyze the estimated equation's residuals. Do they suggest that the regression equation is adequate? If not, return to part b and revise your equation. Con- tinue to revise the equation until the results are satisfactory. d.Use your final equation to predict the peak power load on a summer day with a high temperature of 100 degrees.

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