Date Sales Jan-06 20390.7 Feb-06 24538.21 Mar-06 23306.99 Apr-06 24829 May-06 20418.38 Jun-06 19568.24 Jul-06 16672.24 Aug-06 13334.3 Sep-06 13274.2 Oct-06 13609.52 Nov-06 15182.95 Dec-06 28339.15 Jan-07 25033.54 Feb-07 25413.35 Mar-07 28358.3 Apr-07 25318 May-07 22806.42 Jun-07 20118.3 Jul-07 17454.41 Aug-07 14795.09 Sep-07 13654.72 Oct-07 15097.95 Nov-07 18882.86 Dec-07 32409.08 Jan-08 27637.5 Feb-08 27999.92 Mar-08 31342.72 Apr-08 30738.76 May-08 27840.19 Jun-08 24297.9 Jul-08 19001.43 Aug-08 17308.16 Sep-08 14956.92 Oct-08 17245.07 Nov-08 19945.34 Dec-08 33102.89 Jan-09 32514.48 Feb-09 35965.79 Mar-09 34222.86 Apr-09 35678.16 May-09 32829.58 Jun-09 28323.04 Jul-09 24132.14 Aug-09 20704.26 Sep-09 21225.58 Oct-09 21070.43 Nov-09 25378.32 Dec-09 37422.3 Jan-10 37984.3 Feb-10 38898.16 Mar-10 42609.91 Apr-10 41679.34 May-10 37492.29 Jun-10 32881.15 Jul-10 25746.61 Aug-10 24847.91 Sep-10 24664.59 Oct-10 26468.17 Nov-10 27792.55 Dec-10 42377.2 Jan-11 41213.39 Feb-11 44249.42 Mar-11 45941.51 Apr-11 46562.32 May-11 40478.65 Jun-11 35201.92 Jul-11 31812.06 Aug-11 30448.92 Sep-11 27422.95 Oct-11 30626.64 Nov-11 32517.49 Dec-11 49115.68 Jan-12 48717.35 Feb-12 50222.91 Mar-12 51153.57 Apr-12 51944.1 May-12 45651.47 Jun-12 44053.59 Jul-12 38315.55 Aug-12 32995.47 Sep-12 31564.62 Oct-12 33002.91 Nov-12 38888.3 Dec-12 52494.4 Jan-13 54455.74 Feb-13 56156.75 Mar-13 56980.72 Apr-13 55795.6 May-13 52859.52 Jun-13 47416.32 Jul-13 41382.5 Aug-13 39074.42 Sep-13 37688.62 Oct-13 39149.57 Nov-13 43828.97 Dec-13 57956.68 Jan-14 46451.18 Feb-14 52033.61 Mar-14 53087.17 Apr-14 50845.74 May-14 46912.48 Jun-14 42176.08 Jul-14 39328.97 Aug-14 35474.65 Sep-14 33719.66 Oct-14 35793.11 Nov-14 37888.32 Dec-14 54264.5 Jan-15 51825.92 Feb-15 58444.23 Mar-15 58367.43 Apr-15 59691.07 May-15 55663.36 Jun-15 47660.6 Jul-15 44422.5 Aug-15 39965.38 Sep-15 36651.54 Oct-15 38936.41 Nov-15 44493.89 Dec-15 57296.16 Jan-16 62420.9 Feb-16 68507.84 Mar-16 70296.1 Apr-16 69119.52 May-16 61995.5 Jun-16 58076.17 Jul-16 49233.25 Aug-16 45682.58 Sep-16 45361.26 Oct-16 46905.75 Nov-16 50998.52 Dec-16 67110.27 Jan-17 67846.52 Feb-17 73182.04 Mar-17 77474.35 Apr-17 76348.3 May-17 70504.08 Jun-17 62198.12 Jul-17 57197.95 Aug-17 50605.02 Sep-17 48574.69 Oct-17 49450.9 Nov-17 56646.98 Dec-17 74871.97 Jan-18 77466.39 Feb-18 82815.39 Mar-18 85229.82 Apr-18 80452 May-18 75432.45 Jun-18 67678.55 Jul-18 60484.78 Aug-18 55743.79 Sep-18 53563.82 Oct-18 54921.59 Nov-18 61633.87 Dec-18 79360.23 Jan-19 78952.95 Feb-19 84964.32 Mar-19 84121.17 Apr-19 84935.94 May-19 77190.72 Jun-19 69711.04 Jul-19 62582.45 Aug-19 59046.23 Sep-19 54338.92 Oct-19 60068.76 Nov-19 63335.01 Dec-19 82746.34 Jan-20 83340.96 Feb-20 92476.54 Mar-20 91220.63 Apr-20 89700.83 May-20 86964.1 Jun-20 78667.71 Jul-20 70491.49 Aug-20 61965.06 Sep-20 63948.45 Oct-20 63915.06 Nov-20 69688.96 Dec-20 79596.64

R Code Explanation/Questions 1.Summarize the data 2.Plot the data The goal is to forecast next year's sales. Partition the data into training and validation periods 3.Fit a regression model to sales using log(Sales) as the outcome variable (plot the regression fit) 4.Create (and plot) an ACF plot for lag-1 through lag-20 5.Fit an AR model with lag-2 to the forecast errors (plot the model) 6.Examine the ACF plot and the estimated coefficients of the ARIMA(2,0,0) model, comment on the regression forecast 7.Compute forecasts for the upcoming 6 months using the regression and AR(2) models 8.Add the forecasts to the plots of the actual data All codes need to be documented. A self-contained file (word of pdf) that includes all the codes, comments, plots and other outputs must be submitted.