Multiple Linear Regression - Estimated Regression Equation

Y[t] = + 103.708251028807 + 7.79209876543207X[t] -1.25631687242790M1[t] -0.0279835390946507M2[t] + 0.108683127572014M3[t] + 0.140349794238680M4[t] + 0.138683127572013M5[t] + 0.143683127572011M6[t] + 0.413683127572011M7[t] -0.314999999999997M8[t] -0.151666666666663M9[t] -0.0999999999999963M10[t] -0.0416666666666662M11[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)	103.708251028807	2.171404	47.7609	0	0
X	7.79209876543207	1.265432	6.1577	0	0
M1	-1.25631687242790	2.692659	-0.4666	0.642525	0.321263
M2	-0.0279835390946507	2.692659	-0.0104	0.991743	0.495872
M3	0.108683127572014	2.692659	0.0404	0.96794	0.48397
M4	0.140349794238680	2.692659	0.0521	0.958607	0.479303
M5	0.138683127572013	2.692659	0.0515	0.959098	0.479549
M6	0.143683127572011	2.692659	0.0534	0.957625	0.478812
M7	0.413683127572011	2.692659	0.1536	0.878423	0.439211
M8	-0.314999999999997	2.684387	-0.1173	0.906985	0.453493
M9	-0.151666666666663	2.684387	-0.0565	0.955135	0.477567
M10	-0.0999999999999963	2.684387	-0.0373	0.970409	0.485205
M11	-0.0416666666666662	2.684387	-0.0155	0.987668	0.493834

Multiple Linear Regression - Regression Statistics
Multiple R	0.633977059741042
R-squared	0.401926912277897
Adjusted R-squared	0.280284928334419
F-TEST (value)	3.30417919247892
F-TEST (DF numerator)	12
F-TEST (DF denominator)	59
p-value	0.00106190316840671
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	4.64949479158511
Sum Squared Residuals	1275.45030720165

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	103.52	102.451934156378	1.06806584362184
2	103.5	103.680267489712	-0.180267489711939
3	103.52	103.816934156379	-0.296934156378628
4	103.53	103.848600823045	-0.318600823045288
5	103.53	103.846934156379	-0.316934156378624
6	103.53	103.851934156379	-0.321934156378616
7	103.52	104.121934156379	-0.601934156378624
8	103.54	103.393251028807	0.146748971193395
9	103.59	103.55658436214	0.0334156378600592
10	103.59	103.608251028807	-0.0182510288066077
11	103.59	103.66658436214	-0.0765843621399387
12	103.59	103.708251028807	-0.118251028806605
13	103.63	102.451934156379	1.17806584362129
14	103.74	103.680267489712	0.0597325102880376
15	103.7	103.816934156379	-0.116934156378618
16	103.72	103.848600823045	-0.128600823045290
17	103.81	103.846934156379	-0.0369341563786187
18	103.8	103.851934156379	-0.0519341563786220
19	104.22	104.121934156379	0.0980658436213797
20	106.91	111.185349794239	-4.27534979423868
21	107.06	111.348683127572	-4.28868312757201
22	107.17	111.400349794239	-4.23034979423868
23	107.25	111.458683127572	-4.20868312757201
24	107.28	111.500349794239	-4.22034979423868
25	107.24	110.244032921811	-3.00403292181079
26	107.23	111.472366255144	-4.24236625514402
27	107.34	111.609032921811	-4.26903292181069
28	107.34	111.640699588477	-4.30069958847735
29	107.3	111.639032921811	-4.33903292181069
30	107.24	111.644032921811	-4.40403292181069
31	107.3	111.914032921811	-4.61403292181069
32	107.32	111.185349794239	-3.86534979423869
33	107.28	111.348683127572	-4.06868312757201
34	107.33	111.400349794239	-4.07034979423868
35	107.33	111.458683127572	-4.12868312757201
36	107.33	111.500349794239	-4.17034979423868
37	107.28	110.244032921811	-2.96403292181078
38	107.28	111.472366255144	-4.19236625514402
39	107.29	111.609032921811	-4.31903292181069
40	107.29	111.640699588477	-4.35069958847735
41	107.23	111.639032921811	-4.40903292181069
42	107.24	111.644032921811	-4.40403292181069
43	107.24	111.914032921811	-4.67403292181069
44	107.2	111.185349794239	-3.98534979423868
45	107.23	111.348683127572	-4.11868312757201
46	107.2	111.400349794239	-4.20034979423868
47	107.21	111.458683127572	-4.24868312757202
48	107.24	111.500349794239	-4.26034979423868
49	107.21	110.244032921811	-3.03403292181079
50	113.89	111.472366255144	2.41763374485597
51	114.05	111.609032921811	2.44096707818931
52	114.05	111.640699588477	2.40930041152264
53	114.05	111.639032921811	2.41096707818931
54	114.05	111.644032921811	2.40596707818931
55	115.12	111.914032921811	3.20596707818931
56	115.68	111.185349794239	4.49465020576133
57	116.05	111.348683127572	4.70131687242798
58	116.18	111.400349794239	4.77965020576133
59	116.35	111.458683127572	4.89131687242798
60	116.44	111.500349794239	4.93965020576132
61	117	110.244032921811	6.75596707818922
62	117.61	111.472366255144	6.13763374485597
63	118.17	111.609032921811	6.56096707818931
64	118.33	111.640699588477	6.68930041152264
65	118.33	111.639032921811	6.69096707818931
66	118.42	111.644032921811	6.77596707818931
67	118.5	111.914032921811	6.58596707818931
68	118.67	111.185349794239	7.48465020576132
69	119.09	111.348683127572	7.74131687242799
70	119.14	111.400349794239	7.73965020576132
71	119.23	111.458683127572	7.771316872428
72	119.33	111.500349794239	7.82965020576132

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
16	3.05761553116227e-05	6.11523106232454e-05	0.999969423844688
17	1.67616289768937e-06	3.35232579537874e-06	0.999998323837102
18	8.65071151287355e-08	1.73014230257471e-07	0.999999913492885
19	4.42190766381789e-08	8.84381532763578e-08	0.999999955780923
20	1.86561742461450e-09	3.73123484922901e-09	0.999999998134383
21	7.64247020955035e-11	1.52849404191007e-10	0.999999999923575
22	3.20560846422532e-12	6.41121692845065e-12	0.999999999996794
23	1.38580969181783e-13	2.77161938363566e-13	0.999999999999861
24	5.80915115406661e-15	1.16183023081332e-14	0.999999999999994
25	2.0791217265765e-16	4.158243453153e-16	1
26	7.24435287739447e-18	1.44887057547889e-17	1
27	2.98616000440021e-19	5.97232000880043e-19	1
28	1.13290598184980e-20	2.26581196369959e-20	1
29	3.78662500913844e-22	7.57325001827689e-22	1
30	1.28099039044866e-23	2.56198078089732e-23	1
31	6.44130023183776e-25	1.28826004636755e-24	1
32	6.58627463579632e-26	1.31725492715926e-25	1
33	3.28257033663368e-27	6.56514067326736e-27	1
34	1.63406811258701e-28	3.26813622517401e-28	1
35	7.45162305307745e-30	1.49032461061549e-29	1
36	3.39437538610767e-31	6.78875077221533e-31	1
37	1.12001750893996e-32	2.24003501787992e-32	1
38	5.89001857616625e-34	1.17800371523325e-33	1
39	3.52863098029060e-35	7.05726196058119e-35	1
40	2.37896549793899e-36	4.75793099587798e-36	1
41	2.0455254055737e-37	4.0910508111474e-37	1
42	1.94376099665675e-38	3.88752199331351e-38	1
43	5.48634687005665e-39	1.09726937401133e-38	1
44	1.44965644724045e-39	2.89931289448091e-39	1
45	7.67810623754994e-40	1.53562124750999e-39	1
46	1.06083314804767e-39	2.12166629609535e-39	1
47	7.66757483720664e-39	1.53351496744133e-38	1
48	1.27426931324897e-36	2.54853862649794e-36	1
49	4.81602224676094e-34	9.63204449352188e-34	1
50	4.11740315149802e-06	8.23480630299603e-06	0.999995882596848
51	0.00252444260048059	0.00504888520096118	0.99747555739952
52	0.0328437147600731	0.0656874295201463	0.967156285239927
53	0.120597706973997	0.241195413947995	0.879402293026003
54	0.264549251456340	0.529098502912681	0.73545074854366
55	0.369243025913480	0.738486051826961	0.63075697408652
56	0.425177000433599	0.850354000867198	0.574822999566401

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	36	0.878048780487805	NOK
5% type I error level	36	0.878048780487805	NOK
10% type I error level	37	0.902439024390244	NOK