Question: Apply Linear Regression to predict call volume from headcount using the appropriate Excel template. (Linerar_Regression Model.xlsx). Based on the upcoming acquisition of Cutter Corp on

Apply Linear Regression to predict call volume from headcount using the appropriate Excel template. (Linerar_Regression Model.xlsx). Based on the upcoming acquisition of Cutter Corp on 7/1/2015, the forecast of head count for July 2015 is 77,000 (Estimator x value).

Show your forecast below and attach the completed Excel template.

A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 B C D E F G Estimate 6,765 6,453 6,527 8,316 7,252 7,079 7,772 8,745 7,023 6,914 7,878 9,627 Estimation Error 43.85 11.64 42.18 49.93 5.40 14.57 11.66 21.26 31.07 91.70 70.55 23.24 Square of Error 1,923 136 1,780 2,493 29 212 136 452 965 8,408 4,977 540 Template for Linear Regression Time Period 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Independent Variable 4,894 4,703 4,748 5,844 5,192 5,086 5,511 6,107 5,052 4,985 5,576 6,647 Dependent Variable 6,809 6,465 6,569 8,266 7,257 7,064 7,784 8,724 6,992 6,822 7,949 9,650 Avg Est. Error: H I J K L M N O 1 Dependent Variable 2 3 Linear Regression Line Range Name Cells 4 y = a + bx a J5 5 a= -1,223.86 b J6 6 b= 1.63 DependentVariable D5:D34 7 Estimate E5:E34 8 EstimationError F5:F34 9 Estimator IndependentVariable C5:C34 10 If x = 5,000 SquareOfError G5:G34 11 x J10 12 then y= 6,938.18 y J12 13 14 15 12,000 16 17 18 10,000 19 f(x) = 1.63240849219869 x 1223.8603692104 20 21 8,000 22 23 24 6,000 25 26 27 4,000 28 29 30 2,000 31 32 33 0 34 4,500 5,000 5,500 6,000 35 Independent Variable 36 37 38 6,500 7,000

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