Multiple Linear Regression - Estimated Regression Equation

Yt[t] = + 44.9444 + 22.1286000000001M1[t] + 20.0048M2[t] + 30.9002000000000M3[t] + 29.0516M4[t] + 24.918M5[t] + 33.5596M6[t] + 22.7112M7[t] + 15.5694M8[t] + 17.131M9[t] + 19.5426M10[t] + 10.4772M11[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)	44.9444	1.958977	22.9428	0	0
M1	22.1286000000001	2.770412	7.9875	0	0
M2	20.0048	2.770412	7.2209	0	0
M3	30.9002000000000	2.770412	11.1536	0	0
M4	29.0516	2.770412	10.4864	0	0
M5	24.918	2.770412	8.9943	0	0
M6	33.5596	2.770412	12.1136	0	0
M7	22.7112	2.770412	8.1978	0	0
M8	15.5694	2.770412	5.6199	1e-06	0
M9	17.131	2.770412	6.1836	0	0
M10	19.5426	2.770412	7.054	0	0
M11	10.4772	2.770412	3.7818	0.000431	0.000216

Multiple Linear Regression - Regression Statistics
Multiple R	0.914125792852386
R-squared	0.835625965158004
Adjusted R-squared	0.797956915506713
F-TEST (value)	22.1833567051345
F-TEST (DF numerator)	11
F-TEST (DF denominator)	48
p-value	3.5527136788005e-15
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	4.38040539124709
Sum Squared Residuals	921.021666799997

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	63.152	67.0729999999998	-3.9209999999998
2	60.106	64.9492	-4.84320000000002
3	72.616	75.8446	-3.22859999999997
4	73.159	73.996	-0.836999999999917
5	68.848	69.8624	-1.01440000000000
6	77.056	78.504	-1.448
7	62.246	67.6556	-5.40959999999995
8	60.777	60.5138	0.263200000000004
9	64.513	62.0754	2.4376
10	58.353	64.487	-6.13399999999998
11	56.511	55.4216	1.08940000000000
12	44.554	44.9444	-0.390399999999999
13	71.414	67.073	4.34099999999995
14	65.719	64.9492	0.769799999999996
15	80.997	75.8446	5.15239999999999
16	69.826	73.996	-4.17000000000003
17	65.386	69.8624	-4.47640000000001
18	75.589	78.504	-2.915
19	65.52	67.6556	-2.13560000000001
20	59.003	60.5138	-1.51080000000000
21	63.961	62.0754	1.8856
22	59.716	64.487	-4.771
23	57.52	55.4216	2.09840000000000
24	42.886	44.9444	-2.05839999999999
25	69.805	67.073	2.73199999999996
26	64.656	64.9492	-0.293199999999991
27	80.353	75.8446	4.50839999999998
28	71.321	73.996	-2.67500000000002
29	76.577	69.8624	6.7146
30	81.58	78.504	3.076
31	71.127	67.6556	3.47139999999998
32	63.478	60.5138	2.9642
33	48.152	62.0754	-13.9234
34	69.236	64.487	4.749
35	57.038	55.4216	1.61640000000000
36	43.621	44.9444	-1.32339999999999
37	69.551	67.073	2.47799999999995
38	72.009	64.9492	7.0598
39	72.14	75.8446	-3.70460000000001
40	81.519	73.996	7.52299999999998
41	73.31	69.8624	3.4476
42	80.406	78.504	1.90200000000000
43	70.697	67.6556	3.04139999999999
44	59.328	60.5138	-1.1858
45	68.281	62.0754	6.2056
46	70.041	64.487	5.55399999999999
47	51.244	55.4216	-4.1776
48	46.538	44.9444	1.59360000000000
49	61.443	67.073	-5.63000000000005
50	62.256	64.9492	-2.69320000000000
51	73.117	75.8446	-2.72760000000001
52	74.155	73.996	0.158999999999981
53	65.191	69.8624	-4.6714
54	77.889	78.504	-0.615000000000005
55	68.688	67.6556	1.03239999999999
56	59.983	60.5138	-0.530800000000005
57	65.47	62.0754	3.3946
58	65.089	64.487	0.601999999999994
59	54.795	55.4216	-0.626599999999998
60	47.123	44.9444	2.17860000000000

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
15	0.7079254543835	0.584149091233001	0.292074545616500
16	0.598632615585548	0.802734768828904	0.401367384414452
17	0.50581728413384	0.98836543173232	0.49418271586616
18	0.385067664693177	0.770135329386353	0.614932335306823
19	0.305643231968512	0.611286463937024	0.694356768031488
20	0.213310188775333	0.426620377550665	0.786689811224667
21	0.14081798106397	0.28163596212794	0.85918201893603
22	0.112682974329797	0.225365948659593	0.887317025670203
23	0.071204668503109	0.142409337006218	0.928795331496891
24	0.0442307507948804	0.0884615015897608	0.95576924920512
25	0.0308099725426622	0.0616199450853244	0.969190027457338
26	0.0183202547448469	0.0366405094896937	0.981679745255153
27	0.0185792264892524	0.0371584529785049	0.981420773510748
28	0.0128142180789059	0.0256284361578118	0.987185781921094
29	0.0591202975027376	0.118240595005475	0.940879702497262
30	0.0552923481881774	0.110584696376355	0.944707651811823
31	0.0662128838856106	0.132425767771221	0.933787116114389
32	0.0519375927799288	0.103875185559858	0.948062407220071
33	0.815301177577278	0.369397644845443	0.184698822422722
34	0.833612831564939	0.332774336870122	0.166387168435061
35	0.795903557090928	0.408192885818145	0.204096442909072
36	0.739675508381914	0.520648983236171	0.260324491618086
37	0.782044984557372	0.435910030885256	0.217955015442628
38	0.920926458966514	0.158147082066971	0.0790735410334856
39	0.884343985337348	0.231312029325305	0.115656014662652
40	0.94627634556065	0.107447308878698	0.053723654439349
41	0.98765532406194	0.0246893518761182	0.0123446759380591
42	0.97718610767188	0.0456277846562400	0.0228138923281200
43	0.95473977644012	0.0905204471197598	0.0452602235598799
44	0.894889842269555	0.21022031546089	0.105110157730445
45	0.839875973578812	0.320248052842376	0.160124026421188

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	5	0.161290322580645	NOK
10% type I error level	8	0.258064516129032	NOK