1. Forecasting With Dummy Variables Group 6 Evin Whittington Travis Menn

2. Case 15.1 The Vintage Restaurant, on Captiva Island near Fort Myers, Florida, is owned and operated by Karen Payne. The restaurant just completed its third year of operation. During that time, Karen sought to establish a reputation for the restaurant as a high-quality dining establish-ment that specializes in fresh seafood. Through the efforts of Karen and her staff, her restaurant has become one of the best and fastest-growing restaurants on the island.

3. Past Sales Data MonthFirst YearSecond YearThird Year January242263282 February235238255 March232247265 April178193205 May184183210 June140149160 July145157166 August152161174 September110122126 October130103148 November152167173 December206230235

4. Time plot of the Data

5. Time series plot The time series plot shows higher sales in the beginning of the year. The sales dip the their low point around the month of November. This shows a seasonal pattern in the sales.

6. Dummy Variables To forecast the next year of sales we use dummy variables. Example of Dummy Variables Month1 = 1 if January, 0 otherwise Month2 = 1 if February, 0 otherwise And so on

7. Regression of dummy variables.

8. Forecasting With the Summary Output we are able to forecast the next 12 months of sales. Forecast:

9. Forecast Error. The actual sales for January were $295 which gave us a forecasting error of $128.09 Reasons for that could be the raw data still has seasonal trends in it. There also could be some 3 rd part factors affecting sales.