Multiple Linear Regression - Estimated Regression Equation

Y[t] = + 52.016 -1.57600000000002M1[t] -4.512M2[t] -5.208M3[t] -4.854M4[t] -2.676M5[t] + 0.241999999999999M6[t] + 1.95M7[t] + 3.69M8[t] + 3.384M9[t] + 2.4M10[t] + 1.048M11[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)	52.016	4.386011	11.8595	0	0
M1	-1.57600000000002	6.202756	-0.2541	0.800519	0.400259
M2	-4.512	6.202756	-0.7274	0.470503	0.235251
M3	-5.208	6.202756	-0.8396	0.40528	0.20264
M4	-4.854	6.202756	-0.7826	0.437732	0.218866
M5	-2.676	6.202756	-0.4314	0.668094	0.334047
M6	0.241999999999999	6.202756	0.039	0.96904	0.48452
M7	1.95	6.202756	0.3144	0.754598	0.377299
M8	3.69	6.202756	0.5949	0.554707	0.277353
M9	3.384	6.202756	0.5456	0.587892	0.293946
M10	2.4	6.202756	0.3869	0.700522	0.350261
M11	1.048	6.202756	0.169	0.86654	0.43327

Multiple Linear Regression - Regression Statistics
Multiple R	0.330671852624358
R-squared	0.109343874118025
Adjusted R-squared	-0.094764821396594
F-TEST (value)	0.535713943212153
F-TEST (DF numerator)	11
F-TEST (DF denominator)	48
p-value	0.869091752881583
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	9.80741828073695
Sum Squared Residuals	4616.90176

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	47.54	50.4400000000001	-2.90000000000007
2	45.31	47.504	-2.194
3	46.9	46.808	0.0919999999999967
4	47.16	47.162	-0.00200000000000268
5	48.24	49.34	-1.1
6	52.7	52.258	0.442000000000003
7	51.72	53.966	-2.246
8	51.5	55.706	-4.206
9	52.45	55.4	-2.95
10	53	54.416	-1.416
11	48.36	53.064	-4.704
12	46.63	52.016	-5.386
13	45.92	50.44	-4.51999999999998
14	45.53	47.504	-1.974
15	42.17	46.808	-4.638
16	43.66	47.162	-3.502
17	45.32	49.34	-4.02
18	47.43	52.258	-4.828
19	47.76	53.966	-6.206
20	49.49	55.706	-6.216
21	50.69	55.4	-4.71
22	49.8	54.416	-4.616
23	52.13	53.064	-0.933999999999997
24	53.94	52.016	1.924
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	50.44	1.94000000000002
38	42.37	47.504	-5.134
39	39.83	46.808	-6.978
40	38.79	47.162	-8.372
41	37.33	49.34	-12.01
42	39.4	52.258	-12.858
43	39.45	53.966	-14.516
44	43.24	55.706	-12.466
45	42.33	55.4	-13.07
46	45.5	54.416	-8.916
47	43.44	53.064	-9.624
48	43.88	52.016	-8.136
49	45.61	50.44	-4.82999999999998
50	45.12	47.504	-2.384
51	47.56	46.808	0.752000000000003
52	47.04	47.162	-0.121999999999997
53	51.07	49.34	1.73
54	54.72	52.258	2.462
55	55.37	53.966	1.404
56	55.39	55.706	-0.316
57	53.13	55.4	-2.27
58	53.71	54.416	-0.705999999999998
59	54.59	53.064	1.526
60	54.61	52.016	2.594

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
15	0.00754306650143444	0.0150861330028689	0.992456933498566
16	0.00231920435004474	0.00463840870008947	0.997680795649955
17	0.000592129497563981	0.00118425899512796	0.999407870502436
18	0.000367817161777738	0.000735634323555477	0.999632182838222
19	0.000131941218358315	0.00026388243671663	0.999868058781642
20	3.04473499258097e-05	6.08946998516194e-05	0.999969552650074
21	6.39228931629099e-06	1.2784578632582e-05	0.999993607710684
22	1.8017560271664e-06	3.6035120543328e-06	0.999998198243973
23	5.8095712321055e-07	1.1619142464211e-06	0.999999419042877
24	7.8330682534243e-07	1.56661365068486e-06	0.999999216693175
25	4.03476967523567e-05	8.06953935047134e-05	0.999959652303248
26	0.000221460190973714	0.000442920381947428	0.999778539809026
27	0.000508471629975747	0.00101694325995149	0.999491528370024
28	0.00110464235655415	0.0022092847131083	0.998895357643446
29	0.00458136600925777	0.00916273201851554	0.995418633990742
30	0.0111573001819086	0.0223146003638172	0.98884269981809
31	0.0801814803586919	0.160362960717384	0.919818519641308
32	0.333286279867145	0.66657255973429	0.666713720132855
33	0.721405651857533	0.557188696284933	0.278594348142467
34	0.840211213346461	0.319577573307078	0.159788786653539
35	0.903265640752592	0.193468718494816	0.0967343592474082
36	0.90365980458539	0.192680390829219	0.0963401954146094
37	0.861711002744547	0.276577994510906	0.138288997255453
38	0.800634061685778	0.398731876628444	0.199365938314222
39	0.747330774873058	0.505338450253884	0.252669225126942
40	0.693211670208565	0.61357665958287	0.306788329791435
41	0.703264443624475	0.59347111275105	0.296735556375525
42	0.73938585351622	0.521228292967561	0.260614146483781
43	0.797755543691654	0.404488912616692	0.202244456308346
44	0.790545686185878	0.418908627628244	0.209454313814122
45	0.755849589570002	0.488300820859995	0.244150410429998

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	14	0.451612903225806	NOK
5% type I error level	16	0.516129032258065	NOK
10% type I error level	16	0.516129032258065	NOK