1. Quarterly snow blower sales ($ thousands) along with income ($ billions) are collected from March 2007 through December 2016 ("Snow blower sales data.xlsx")
   1. Using income and seasonality (where the first quarter is the baseline group), fit a regression model to forecast quarterly sales. Provide the equation of the line fit and interpret the slope parameters
   2. Evaluate the model
   3. Check the model assumptions
   4. If income was $650 (billion) during the third quarter, what would be the forecasted snow blower sales?

DATA:

Period	Sales	Income
Mar-07	72962	218
Jun-07	81921	237
Sep-07	97729	263
Dec-07	142161	293
Mar-08	145592	318
Jun-08	117129	359
Sep-08	114159	404
Dec-08	151402	436
Mar-09	153907	475
Jun-09	100144	534
Sep-09	123242	574
Dec-09	128497	622
Mar-10	176076	667
Jun-10	180440	702
Sep-10	162665	753
Dec-10	220818	796
Mar-11	202415	858
Jun-11	211780	870
Sep-11	163710	934
Dec-11	200135	1,010
Mar-12	174200	1,066
Jun-12	182556	1,096
Sep-12	198990	1,162
Dec-12	243700	1,187
Mar-13	253142	1,207
Jun-13	218755	1,242
Sep-13	225422	1,279
Dec-13	253653	1,318
Mar-14	257156	1,346
Jun-14	202568	1,395
Sep-14	224482	1,443
Dec-14	229879	1,528
Mar-15	289321	1,613
Jun-15	266095	1,646
Sep-15	262938	1,694
Dec-15	322052	1,730
Mar-16	313769	1,755
Jun-16	315011	1,842
Sep-16	264939	1,832
Dec-16	301479	1,882