Multiple Linear Regression - Estimated Regression Equation

Y[t] = + 8.0288 -0.321999999999999X[t] -0.144400000000006M1[t] -0.344399999999999M2[t] -0.204399999999999M3[t] + 0.0756000000000006M4[t] + 0.115600000000000M5[t] -0.00439999999999969M6[t] -0.204399999999999M7[t] -0.464399999999999M8[t] -0.564399999999999M9[t] + 0.0556000000000004M10[t] + 0.0956000000000006M11[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)	8.0288	0.316634	25.3567	0	0
X	-0.321999999999999	0.215442	-1.4946	0.141703	0.070851
M1	-0.144400000000006	0.433033	-0.3335	0.740269	0.370134
M2	-0.344399999999999	0.433033	-0.7953	0.430425	0.215213
M3	-0.204399999999999	0.433033	-0.472	0.639097	0.319549
M4	0.0756000000000006	0.433033	0.1746	0.862158	0.431079
M5	0.115600000000000	0.433033	0.267	0.790672	0.395336
M6	-0.00439999999999969	0.433033	-0.0102	0.991936	0.495968
M7	-0.204399999999999	0.433033	-0.472	0.639097	0.319549
M8	-0.464399999999999	0.433033	-1.0724	0.289	0.1445
M9	-0.564399999999999	0.433033	-1.3034	0.198799	0.099399
M10	0.0556000000000004	0.433033	0.1284	0.898383	0.449191
M11	0.0956000000000006	0.433033	0.2208	0.826229	0.413115

Multiple Linear Regression - Regression Statistics
Multiple R	0.387829572007958
R-squared	0.150411776923876
Adjusted R-squared	-0.066504365138113
F-TEST (value)	0.693409791885807
F-TEST (DF numerator)	12
F-TEST (DF denominator)	47
p-value	0.749314651603673
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.68128726718289
Sum Squared Residuals	21.8151599999999

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	8.7	7.88440000000003	0.815599999999974
2	8.2	7.6844	0.5156
3	8.3	7.8244	0.4756
4	8.5	8.1044	0.395600000000000
5	8.6	8.1444	0.4556
6	8.5	8.0244	0.4756
7	8.2	7.8244	0.375599999999999
8	8.1	7.5644	0.5356
9	7.9	7.4644	0.435600000000000
10	8.6	8.0844	0.5156
11	8.7	8.1244	0.575599999999999
12	8.7	8.0288	0.6712
13	8.5	7.8844	0.615600000000007
14	8.4	7.6844	0.7156
15	8.5	7.8244	0.6756
16	8.7	8.1044	0.5956
17	8.7	8.1444	0.5556
18	8.6	8.0244	0.5756
19	8.5	7.8244	0.6756
20	8.3	7.5644	0.7356
21	8	7.4644	0.5356
22	8.2	8.0844	0.115600000000000
23	8.1	8.1244	-0.0244000000000003
24	8.1	8.0288	0.0712000000000006
25	8	7.8844	0.115600000000007
26	7.9	7.6844	0.2156
27	7.9	7.8244	0.0756000000000002
28	8	8.1044	-0.1044
29	8	8.1444	-0.144400000000000
30	7.9	8.0244	-0.124399999999999
31	8	7.8244	0.175600
32	7.7	7.5644	0.135600000000000
33	7.2	7.4644	-0.2644
34	7.5	8.0844	-0.5844
35	7.3	8.1244	-0.8244
36	7	8.0288	-1.02880000000000
37	7	7.8844	-0.884399999999993
38	7	7.6844	-0.6844
39	7.2	7.8244	-0.6244
40	7.3	8.1044	-0.8044
41	7.1	8.1444	-1.0444
42	6.8	8.0244	-1.2244
43	6.4	7.8244	-1.4244
44	6.1	7.5644	-1.4644
45	6.5	7.4644	-0.9644
46	7.7	8.0844	-0.384399999999999
47	7.9	8.1244	-0.224400000000000
48	7.5	7.7068	-0.2068
49	6.9	7.5624	-0.662399999999994
50	6.6	7.3624	-0.762400000000001
51	6.9	7.5024	-0.6024
52	7.7	7.7824	-0.0824000000000005
53	8	7.8224	0.177600000000000
54	8	7.7024	0.297599999999999
55	7.7	7.5024	0.197600000000000
56	7.3	7.2424	0.0575999999999991
57	7.4	7.1424	0.257600000000000
58	8.1	7.7624	0.337599999999999
59	8.3	7.8024	0.4976
60	8.2	7.7068	0.493199999999999

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
16	0.0205188468201001	0.0410376936402003	0.9794811531799
17	0.00506218856671496	0.0101243771334299	0.994937811433285
18	0.00126809325832566	0.00253618651665131	0.998731906741674
19	0.00093863250915197	0.00187726501830394	0.999061367490848
20	0.000469061050603817	0.000938122101207633	0.999530938949396
21	0.000159323662258763	0.000318647324517526	0.99984067633774
22	0.000204972915216014	0.000409945830432028	0.999795027084784
23	0.000654781371272177	0.00130956274254435	0.999345218628728
24	0.00128952582531370	0.00257905165062740	0.998710474174686
25	0.00397528651671241	0.00795057303342481	0.996024713483288
26	0.00606487492833997	0.0121297498566799	0.99393512507166
27	0.0103667916900097	0.0207335833800194	0.98963320830999
28	0.0166221092224031	0.0332442184448062	0.983377890777597
29	0.0264923071931726	0.0529846143863452	0.973507692806827
30	0.0403781466080727	0.0807562932161453	0.959621853391927
31	0.0721659139091055	0.144331827818211	0.927834086090894
32	0.20048093260975	0.4009618652195	0.79951906739025
33	0.273126119506474	0.546252239012948	0.726873880493526
34	0.321979242662475	0.64395848532495	0.678020757337525
35	0.456223258794996	0.912446517589991	0.543776741205004
36	0.59077750527719	0.81844498944562	0.40922249472281
37	0.727002806262114	0.545994387475772	0.272997193737886
38	0.868874993714035	0.262250012571931	0.131125006285965
39	0.960635504714138	0.0787289905717236	0.0393644952858618
40	0.95913537561909	0.0817292487618181	0.0408646243809090
41	0.93703328422819	0.125933431543620	0.0629667157718102
42	0.91818946902091	0.163621061958181	0.0818105309790905
43	0.913902749679675	0.17219450064065	0.086097250320325
44	0.902089225675967	0.195821548648067	0.0979107743240333

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	8	0.275862068965517	NOK
5% type I error level	13	0.448275862068966	NOK
10% type I error level	17	0.586206896551724	NOK