Please help me with my case study. I need to do this in Excel. Please give me specific instructions. There are TWO data sets (Attached at the end). i dont know when to use which. Whoever can answer this, I would love to chat about tutoring (paid). Thank you!

Week 3 Case Study (Case Study #2)

HeathCo is a manufacturing company that produces a line of skiwear that is sold under various brand names. The Product Manager of HeathCo has contracted with you to develop a model to forecast company sales. You will be supplied with quarterly sales data from 2007 through 2016. They want a model that will allow them to forecast sales one year (four quarters) out.You will use the HeathCo Sales Data worksheet in the HeathCo_Sales.xlsx workbook for this case study. In this case study, you will run a trend regression model and compare the results to the best fitting model from the previous case study(s).

1. Trend Regression Model
   1. Use the data from the years 2007 to 2015 to create a trend regression model using ForecastX. Reserve 2016 data as a holdout to evaluate the accuracy of your models.
      1. On the Data Capture tab, make sure the Data to be Forecastonly includes data through 2015 (Row 37) and set the Forecast Periods to 4.
      2. On the Forecast Method tab, set the Forecast Technique to Trend (Linear) Regression.
      3. On the Statistics tab, check the MAPE option on the tab and the Root Mean Sq Error on the Accuracy tab of the More Statistics pop-up option.
      4. On the Reports tab, uncheck the Standard option, check the Audit option, and check the Fitted Values Table option.
      5. Press Finish and View Output. Save your results. Copy the results worksheet to a workbook with the data file.
   2. Based on a review of the model fit graph in ForecastX, do the model results show a similar trend to the trend of data series?Explain your answer. Write your answer in the box below.

1. Based on a review of the model fit graph in ForecastX, do the model results show a similar seasonal pattern to the seasonal pattern of data series? Explain your answer. Write your answer in the box below.

1. Write a brief description of the model fit using the ForecastX MAPE and RMSE output. Include the values of the MAPE and RMSE measures in your description. Write your answer in the box below.

1. Calculate the MAPE and RMSE model accuracy using the four quarters of holdout data and the forecasts for the same four quarters in the ForecastX output. Label your results in an Excel workbook using the prompt number.
2. Write a brief description of the model accuracy. Include the values of the MAPE and RMSE measures in your description. Write your answer in the box below.

1. Best Fitting Model
   1. Is the model fit of the trend regression model better than the best fitting model from the previous case study(s) based on MAPE? Explain your answer using the MAPE model fit values. Write your answer in the box below.

1. Is the model fit of the trend regression model better than the best fitting model from the previous case study(s) based on RMSE? Explain your answer using the RMSE model fit values. Write your answer in the box below.

Health Co. Sales Data

Period	Sales
Mar-07	72962
Jun-07	81921
Sep-07	97729
Dec-07	142161
Mar-08	145592
Jun-08	117129
Sep-08	114159
Dec-08	151402
Mar-09	153907
Jun-09	100144
Sep-09	123242
Dec-09	128497
Mar-10	176076
Jun-10	180440
Sep-10	162665
Dec-10	220818
Mar-11	202415
Jun-11	211780
Sep-11	163710
Dec-11	200135
Mar-12	174200
Jun-12	182556
Sep-12	198990
Dec-12	243700
Mar-13	253142
Jun-13	218755
Sep-13	225422
Dec-13	253653
Mar-14	257156
Jun-14	202568
Sep-14	224482
Dec-14	229879
Mar-15	289321
Jun-15	266095
Sep-15	262938
Dec-15	322052
Mar-16	313769
Jun-16	315011
Sep-16	264939
Dec-16	301479

Health Co Data with Casual Vars

Period	Sales	Income	UnempRate	Time	Q2	Q3	Q4
Mar-07	72962	218	8.4	1	0	0	0
Jun-07	81921	237	8.2	2	1	0	0
Sep-07	97729	263	8.4	3	0	1	0
Dec-07	142161	293	8.4	4	0	0	1
Mar-08	145592	318	8.1	5	0	0	0
Jun-08	117129	359	7.7	6	1	0	0
Sep-08	114159	404	7.5	7	0	1	0
Dec-08	151402	436	7.2	8	0	0	1
Mar-09	153907	475	6.9	9	0	0	0
Jun-09	100144	534	6.5	10	1	0	0
Sep-09	123242	574	6.5	11	0	1	0
Dec-09	128497	622	6.4	12	0	0	1
Mar-10	176076	667	6.3	13	0	0	0
Jun-10	180440	702	6.2	14	1	0	0
Sep-10	162665	753	6.3	15	0	1	0
Dec-10	220818	796	6.5	16	0	0	1
Mar-11	202415	858	6.8	17	0	0	0
Jun-11	211780	870	7.9	18	1	0	0
Sep-11	163710	934	8.3	19	0	1	0
Dec-11	200135	1010	8	20	0	0	1
Mar-12	174200	1066	8	21	0	0	0
Jun-12	182556	1096	8	22	1	0	0
Sep-12	198990	1162	8	23	0	1	0
Dec-12	243700	1187	8.9	24	0	0	1
Mar-13	253142	1207	9.6	25	0	0	0
Jun-13	218755	1242	10.2	26	1	0	0
Sep-13	225422	1279	10.7	27	0	1	0
Dec-13	253653	1318	11.5	28	0	0	1
Mar-14	257156	1346	11.2	29	0	0	0
Jun-14	202568	1395	11	30	1	0	0
Sep-14	224482	1443	10.1	31	0	1	0
Dec-14	229879	1528	9.2	32	0	0	1
Mar-15	289321	1613	8.5	33	0	0	0
Jun-15	266095	1646	8	34	1	0	0
Sep-15	262938	1694	8	35	0	1	0
Dec-15	322052	1730	7.9	36	0	0	1
Mar-16	313769	1755	7.9	37	0	0	0
Jun-16	315011	1842	7.9	38	1	0	0
Sep-16	264939	1832	7.8	39	0	1	0
Dec-16	301479	1882	7.6	40	0	0	1