A company has estimated a regression equation to determine the effect of various predictor variables on the demand for electricity sales. Prepare a series of regression estimates and discuss the results using the quarterly data for electrical sales given in the data table below. Complete parts a through c below. Click the icon to view the data table. C... a. Estimate a regression equation with electricity sales as the dependent variable, using the number of customers and the price as predictor variables. Interpret the coefficients. Determine the multiple regression equation. Let Ŷ be estimated electricity sales, X₁ be the number of customers, and X₂ be the price. ý = (D + (Dx + ( X, (Type integers or decimals rounded to one decimal place as needed.)
Electricity_Sales, Number_of_Customers, Price, Degree_Days
1,144,781 690,044.7 6.7651 547.4338
1,143,784 693,866.5 6.8928 -26.3267
1,184,600 697,890.9 6.8626 -1.6835
1,139,054 701,234.3 6.2738 12.4116
1,204,495 704,746.5 6.1591 606.3047
1,179,366 709,583.7 6.2017 148.1826
1,085,489 713,389.1 6.5480 -2.0032
1,160,943 717,401.4 5.9404 -83.5602
1,158,592 721,355.7 5.8960 66.9503
1,193,556 724,228.1 6.0853 24.2879
1,202,514 727,191.2 6.2554 -0.9467
1,174,335 729,230.4 6.3808 -56.3871
1,174,335 731,584.4 6.2768 -360.9842
1,161,770 734,456.2 6.5243 -192.4087
1,142,863 737,848.2 6.4216 -2.8573
1,196,627 739,084.7 6.2837 -168.6407
1,236,468 740,332.7 6.1659 551.9068
1,188,673 741,904.4 6.0801 55.7721
1,181,075 743,467.6 6.9015 -2.5041
1,203,114 743,895.9 6.4296 -159.8219
1,168,515 745,209.2 6.9283 -610.3438
1,224,423 748,664.4 6.4846 113.5806
1,417,430 751,690.6 6.2845 1.2786
1,255,205 755,482.9 6.9084 96.0549
1,251,512 758,648.6 6.8695 251.5787
1,245,558 762,147.7 6.3565 29.6604
Step by step
Solved in 2 steps with 2 images
