Consider the data on new orders for computers and electronic

Consider the data on new orders for computers and electronic products and the M1 money supply for the years 2011 through 2014.

Year

Month

New Orders for Computers and Electronic Products

M-1 Money Supply

2011

1

19222

1855.6

2011

2

20727

1874.7

2011

3

24893

1892.0

2011

4

19375

1897.8

2011

5

20152

1934.3

2011

6

25075

1947.0

2011

7

18615

2001.5

2011

8

21289

2112.9

2011

9

27014

2126.0

2011

10

22179

2137.4

2011

11

20761

2172.0

2011

12

27818

2168.2

2012

1

19447

2202.3

2012

2

23043

2212.2

2012

3

26734

2228.7

2012

4

21897

2245.3

2012

5

22403

2251.0

2012

6

24942

2262.3

2012

7

19365

2314.6

2012

8

20240

2346.5

2012

9

25478

2383.6

2012

10

20790

2415.5

2012

11

20362

2423.2

2012

12

27841

2457.7

2013

1

17393

2467.6

2013

2

18725

2470.4

2013

3

22919

2474.8

2013

4

19560

2511.0

2013

5

20333

2522.0

2013

6

24619

2517.9

2013

7

18065

2545.6

2013

8

18487

2557.3

2013

9

24877

2578.8

2013

10

20410

2620.2

2013

11

20194

2622.2

2013

12

24955

2654.5

Develop a time series decomposition forecast for the computer and electronic products. You must first determine the seasonal (monthly indexes) and then divide the data by these indices. Then using the deseasonalized data, determine the trend. Finally, you must re-seasonalize the data.

Year	Month	New Orders for Computers and Electronic Products	M-1 Money Supply
2011	1	19222	1855.6
2011	2	20727	1874.7
2011	3	24893	1892.0
2011	4	19375	1897.8
2011	5	20152	1934.3
2011	6	25075	1947.0
2011	7	18615	2001.5
2011	8	21289	2112.9
2011	9	27014	2126.0
2011	10	22179	2137.4
2011	11	20761	2172.0
2011	12	27818	2168.2
2012	1	19447	2202.3
2012	2	23043	2212.2
2012	3	26734	2228.7
2012	4	21897	2245.3
2012	5	22403	2251.0
2012	6	24942	2262.3
2012	7	19365	2314.6
2012	8	20240	2346.5
2012	9	25478	2383.6
2012	10	20790	2415.5
2012	11	20362	2423.2
2012	12	27841	2457.7
2013	1	17393	2467.6
2013	2	18725	2470.4
2013	3	22919	2474.8
2013	4	19560	2511.0
2013	5	20333	2522.0
2013	6	24619	2517.9
2013	7	18065	2545.6
2013	8	18487	2557.3
2013	9	24877	2578.8
2013	10	20410	2620.2
2013	11	20194	2622.2
2013	12	24955	2654.5

Solution

Slope -0.68264 Intercept 49990.33 Year Month Date New Orders for Computers and Electronic Products M-1 Money Supply Identifier Trend Seasonal Avg Seasonal Forecast 2011 1 Jan-11 19222 1855.6 1 22313 -3091 -3376 18937 2011 2 Feb-11 20727 1874.7 2 22292 -1565 -1211 21081 2011 3 Mar-11 24893 1892 3 22273 2620 2825 25098 2011 4 Apr-11 19375 1897.8 4 22252 -2877 -1725 20527 2011 5 May-11 20152 1934.3 5 22231 -2079 -1019 21212 2011 6 Jun-11 25075 1947 6 22210 2865 2918 25128 2011 7 Jul-11 18615 2001.5 7 22190 -3575 -3258 18931 2011 8 Aug-11 21289 2112.9 8 22168 -879 -1914 20255 2011 9 Sep-11 27014 2126 9 22147 4867 3892 26039 2011 10 Oct-11 22179 2137.4 10 22127 52 -751 21376 2011 11 Nov-11 20761 2172 11 22106 -1345 -1417 20689 2011 12 Dec-11 27818 2168.2 12 22085 5733 5036 27121 2012 1 Jan-12 19447 2202.3 1 22064 -2617 -3376 18688 2012 2 Feb-12 23043 2212.2 2 22043 1000 -1211 20832 2012 3 Mar-12 26734 2228.7 3 22023 4711 2825 24848 2012 4 Apr-12 21897 2245.3 4 22002 -105 -1725 20277 2012 5 May-12 22403 2251 5 21981 422 -1019 20962 2012 6 Jun-12 24942 2262.3 6 21960 2982 2918 24878 2012 7 Jul-12 19365 2314.6 7 21940 -2575 -3258 18681 2012 8 Aug-12 20240 2346.5 8 21919 -1679 -1914 20005 2012 9 Sep-12 25478 2383.6 9 21897 3581 3892 25789 2012 10 Oct-12 20790 2415.5 10 21877 -1087 -751 21126 2012 11 Nov-12 20362 2423.2 11 21856 -1494 -1417 20439 2012 12 Dec-12 27841 2457.7 12 21835 6006 5036 26871 2013 1 Jan-13 17393 2467.6 1 21814 -4421 -3376 18438 2013 2 Feb-13 18725 2470.4 2 21793 -3068 -1211 20582 2013 3 Mar-13 22919 2474.8 3 21774 1145 2825 24599 2013 4 Apr-13 19560 2511 4 21753 -2193 -1725 20028 2013 5 May-13 20333 2522 5 21732 -1399 -1019 20713 2013 6 Jun-13 24619 2517.9 6 21711 2908 2918 24629 2013 7 Jul-13 18065 2545.6 7 21691 -3626 -3258 18432 2013 8 Aug-13 18487 2557.3 8 21669 -3182 -1914 19756 2013 9 Sep-13 24877 2578.8 9 21648 3229 3892 25540 2013 10 Oct-13 20410 2620.2 10 21628 -1218 -751 20877 2013 11 Nov-13 20194 2622.2 11 21607 -1413 -1417 20190 2013 12 Dec-13 24955 2654.5 12 21586 3369 5036 26622