Multiple Linear Regression - Estimated Regression Equation

Y[t] = + 52.343 -1.67591666666668M1[t] -4.60283333333333M2[t] -5.28975M3[t] -4.92666666666667M4[t] -2.73958333333334M5[t] + 0.1875M6[t] + 1.90458333333333M7[t] + 3.65366666666667M8[t] + 3.35675M9[t] + 2.38183333333333M10[t] + 1.03891666666667M11[t] -0.0090833333333332t + 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)	52.343	5.196676	10.0724	0	0
M1	-1.67591666666668	6.322048	-0.2651	0.792099	0.396049
M2	-4.60283333333333	6.312602	-0.7291	0.469528	0.234764
M3	-5.28975	6.304044	-0.8391	0.405659	0.202829
M4	-4.92666666666667	6.296376	-0.7825	0.437869	0.218934
M5	-2.73958333333334	6.289604	-0.4356	0.66514	0.33257
M6	0.1875	6.283728	0.0298	0.976322	0.488161
M7	1.90458333333333	6.278752	0.3033	0.762971	0.381486
M8	3.65366666666667	6.274677	0.5823	0.563156	0.281578
M9	3.35675	6.271507	0.5352	0.595009	0.297504
M10	2.38183333333333	6.269241	0.3799	0.705713	0.352857
M11	1.03891666666667	6.267881	0.1658	0.869063	0.434531
t	-0.0090833333333332	0.075385	-0.1205	0.904607	0.452304

Multiple Linear Regression - Regression Statistics
Multiple R	0.33108746990791
R-squared	0.109618912730021
Adjusted R-squared	-0.117712428700611
F-TEST (value)	0.482198855820635
F-TEST (DF numerator)	12
F-TEST (DF denominator)	47
p-value	0.915130339062477
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	9.90967294477171
Sum Squared Residuals	4615.47604

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	47.54	50.6580000000001	-3.11800000000007
2	45.31	47.722	-2.41199999999999
3	46.9	47.026	-0.126
4	47.16	47.38	-0.22
5	48.24	49.558	-1.31799999999999
6	52.7	52.476	0.224000000000006
7	51.72	54.184	-2.464
8	51.5	55.924	-4.424
9	52.45	55.618	-3.16799999999999
10	53	54.634	-1.63399999999999
11	48.36	53.282	-4.922
12	46.63	52.234	-5.604
13	45.92	50.549	-4.62899999999998
14	45.53	47.613	-2.08299999999999
15	42.17	46.917	-4.747
16	43.66	47.271	-3.611
17	45.32	49.449	-4.129
18	47.43	52.367	-4.937
19	47.76	54.075	-6.315
20	49.49	55.815	-6.325
21	50.69	55.509	-4.819
22	49.8	54.525	-4.725
23	52.13	53.173	-1.043
24	53.94	52.125	1.815
25	60.75	50.44	10.31
26	59.19	47.504	11.686
27	57.58	46.808	10.772
28	59.16	47.162	11.998
29	64.74	49.34	15.4
30	67.04	52.258	14.782
31	75.53	53.966	21.564
32	78.91	55.706	23.204
33	78.4	55.4	23
34	70.07	54.416	15.654
35	66.8	53.064	13.736
36	61.02	52.016	9.004
37	52.38	50.331	2.04900000000002
38	42.37	47.395	-5.025
39	39.83	46.699	-6.869
40	38.79	47.053	-8.263
41	37.33	49.231	-11.901
42	39.4	52.149	-12.749
43	39.45	53.857	-14.407
44	43.24	55.597	-12.357
45	42.33	55.291	-12.961
46	45.5	54.307	-8.807
47	43.44	52.955	-9.515
48	43.88	51.907	-8.027
49	45.61	50.222	-4.61199999999999
50	45.12	47.286	-2.166
51	47.56	46.59	0.97
52	47.04	46.944	0.096
53	51.07	49.122	1.948
54	54.72	52.04	2.67999999999999
55	55.37	53.748	1.62199999999999
56	55.39	55.488	-0.0980000000000038
57	53.13	55.182	-2.052
58	53.71	54.198	-0.488000000000001
59	54.59	52.846	1.744
60	54.61	51.798	2.812

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
16	0.00324452342321297	0.00648904684642594	0.996755476576787
17	0.000366084423135861	0.000732168846271721	0.999633915576864
18	9.24489227592348e-05	0.00018489784551847	0.99990755107724
19	1.25919998219168e-05	2.51839996438336e-05	0.999987408000178
20	1.86404837771764e-06	3.72809675543528e-06	0.999998135951622
21	2.90114981394929e-07	5.80229962789857e-07	0.999999709885019
22	3.94367717428555e-08	7.8873543485711e-08	0.999999960563228
23	6.11942359944378e-07	1.22388471988876e-06	0.99999938805764
24	9.41230539502044e-06	1.88246107900409e-05	0.999990587694605
25	0.000589289885324769	0.00117857977064954	0.999410710114675
26	0.00129231285823392	0.00258462571646785	0.998707687141766
27	0.00123522542212894	0.00247045084425788	0.998764774577871
28	0.00103740806870018	0.00207481613740037	0.9989625919313
29	0.001513520857597	0.00302704171519401	0.998486479142403
30	0.0014677773801284	0.00293555476025679	0.998532222619872
31	0.00681973853657771	0.0136394770731554	0.993180261463422
32	0.0330408840625003	0.0660817681250006	0.9669591159375
33	0.145224012310814	0.290448024621627	0.854775987689186
34	0.263897683277766	0.527795366555532	0.736102316722234
35	0.565668009021137	0.868663981957726	0.434331990978863
36	0.949241384708272	0.101517230583456	0.0507586152917282
37	0.999009396686732	0.0019812066265349	0.000990603313267448
38	0.99991576754796	0.000168464904080499	8.42324520402495e-05
39	0.99992183626436	0.000156327471279261	7.81637356396307e-05
40	0.999909592917656	0.000180814164688904	9.0407082344452e-05
41	0.999742808199005	0.000514383601990492	0.000257191800995246
42	0.99954061260218	0.000918774795639888	0.000459387397819944
43	0.999836490975601	0.000327018048797228	0.000163509024398614
44	0.999128935202185	0.00174212959562952	0.00087106479781476

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	23	0.793103448275862	NOK
5% type I error level	24	0.827586206896552	NOK
10% type I error level	25	0.862068965517241	NOK