Multiple Linear Regression - Estimated Regression Equation

y[t] = + 601.951152073733 + 1.24423963133640x[t] -18.9880184331796M1[t] -24.1953917050691M2[t] -40.7465437788018M3[t] -39M4[t] -37.2488479262673M5[t] -41M6[t] -50.9953917050691M7[t] -57.9953917050691M8[t] -64.8976958525346M9[t] -64.9953917050692M10[t] -10.4000000000000M11[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	601.951152073733	15.458534	38.9397	0	0
x	1.24423963133640	12.678314	0.0981	0.92223	0.461115
M1	-18.9880184331796	22.153819	-0.8571	0.395649	0.197825
M2	-24.1953917050691	23.831633	-1.0153	0.315071	0.157535
M3	-40.7465437788018	22.867873	-1.7818	0.081105	0.040552
M4	-39	21.565559	-1.8084	0.076805	0.038402
M5	-37.2488479262673	21.714118	-1.7154	0.092718	0.046359
M6	-41	21.565559	-1.9012	0.063291	0.031646
M7	-50.9953917050691	23.831633	-2.1398	0.037481	0.01874
M8	-57.9953917050691	23.831633	-2.4335	0.018725	0.009362
M9	-64.8976958525346	22.153819	-2.9294	0.005183	0.002592
M10	-64.9953917050692	23.831633	-2.7273	0.008892	0.004446
M11	-10.4000000000000	21.565559	-0.4823	0.63182	0.31591

Multiple Linear Regression - Regression Statistics
Multiple R	0.547179904465269
R-squared	0.299405847850621
Adjusted R-squared	0.124257309813276
F-TEST (value)	1.70943960598051
F-TEST (DF numerator)	12
F-TEST (DF denominator)	48
p-value	0.0943120423223625
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	34.0981432300322
Sum Squared Residuals	55808.8018433179

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	523	582.963133640553	-59.9631336405528
2	519	579	-59.9999999999999
3	509	562.448847926267	-53.4488479262673
4	512	564.195391705069	-52.1953917050690
5	519	564.702304147465	-45.7023041474655
6	517	560.951152073733	-43.9511520737328
7	510	552.2	-42.2
8	509	545.2	-36.2
9	501	537.053456221198	-36.0534562211981
10	507	538.2	-31.2000000000000
11	569	591.551152073733	-22.5511520737328
12	580	601.951152073733	-21.9511520737327
13	578	584.20737327189	-6.20737327188945
14	565	579	-14
15	547	561.204608294931	-14.2046082949309
16	555	562.951152073733	-7.95115207373274
17	562	564.702304147465	-2.70230414746545
18	561	560.951152073733	0.0488479262672605
19	555	552.2	2.80000000000001
20	544	545.2	-1.19999999999999
21	537	538.297695852535	-1.29769585253455
22	543	538.2	4.80000000000003
23	594	592.795391705069	1.20460829493088
24	611	601.951152073733	9.04884792626725
25	613	584.20737327189	28.7926267281105
26	611	579	32
27	594	562.448847926267	31.5511520737327
28	595	562.951152073733	32.0488479262673
29	591	564.702304147465	26.2976958525345
30	589	560.951152073733	28.0488479262673
31	584	552.2	31.8
32	573	545.2	27.8
33	567	537.053456221198	29.9465437788018
34	569	538.2	30.8
35	621	591.551152073733	29.4488479262673
36	629	601.951152073733	27.0488479262673
37	628	584.20737327189	43.7926267281105
38	612	579	33
39	595	562.448847926267	32.5511520737327
40	597	562.951152073733	34.0488479262673
41	593	565.946543778802	27.0534562211982
42	590	560.951152073733	29.0488479262673
43	580	552.2	27.8
44	574	545.2	28.8
45	573	538.297695852535	34.7023041474654
46	573	538.2	34.8
47	620	591.551152073733	28.4488479262673
48	626	601.951152073733	24.0488479262673
49	620	584.20737327189	35.7926267281105
50	588	579	9
51	566	562.448847926267	3.55115207373273
52	557	562.951152073733	-5.95115207373274
53	561	565.946543778802	-4.94654377880181
54	549	562.195391705069	-13.1953917050691
55	532	552.2	-20.2
56	526	545.2	-19.2
57	511	538.297695852535	-27.2976958525345
58	499	538.2	-39.2
59	555	591.551152073733	-36.5511520737327
60	565	603.195391705069	-38.1953917050691
61	542	584.20737327189	-42.2073732718895