In this problem we will evaluate a data set of historical data that shows the number of miles driven in the US (in millions) by month from Jan-12 to Sep-18. Our goal is to develop a miles forecast for the next year. We will evaluate several options and pick the best fit. Do the following: Develop a time series graph of the data set and paste it in the template. Make sure it is properly labeled. Create a new column that has the 3-letter abbreviation for the month for each observation. (Hint: this can be done using the Text function in Excel =text(data,"mmm")) Create a sequential variable n that counts the observations (1, 2, 3, ....) Generate dummy variables based on the month abbreviation. Perform a time series partitioning using the last two years (24 months) for validation. Generate 3 different forecasts. o Holt Winter additive (optimize parameters). Be sure to set the frequency to 12. o Holt Winter multiplicative (optimize parameters). o Seasonal regression using the month dummy variables and the observation number as a trend indicator. (Exclude Month_Jan as the base case.

Date Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 Jan-15 Feb-15 Mar-15 Apr-15 May-15 Jun-15 Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 Jul-16 Aug-16 Sep-16 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 Nov-17 Dec-17 Jan-18 Feb-18 Mar-18 Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18

Miles

227,527 218,196 256,166 249,394 260,774 260,376 260,244 264,379 238,867 253,574 240,361 238,709 229,419 215,803 253,026 252,064 263,406 259,980 263,946 268,061 242,536 258,748 240,055 241,237 226,413 213,949 253,424 256,736 266,237 263,459 270,053 268,831 247,688 265,144 241,451 252,271 233,498 217,220 258,017 262,817 270,839 270,574 278,372 272,209 255,090 268,469 248,843 259,424 239,679 223,011 265,147 269,653 277,972 276,991 285,160 279,213 262,039 275,610 255,154 264,778 244,587 226,947 267,355 272,904 283,956 280,537 287,343 283,184 262,673 278,937 257,712 266,535 245,696 226,661 268,479 272,475 286,160 280,875 288,143 286,609 260,555