Multiple Linear Regression - Estimated Regression Equation

Dollar[t] = + 1.3615 + 0.00849999999999968M1[t] + 0.000499999999999861M2[t] + 0.0254999999999998M3[t] + 0.0374999999999998M4[t] + 0.0168999999999998M5[t] + 0.0124999999999998M6[t] + 0.0220999999999998M7[t] + 0.0160999999999998M8[t] + 0.0110999999999998M9[t] + 0.0128999999999998M10[t] -0.00770000000000014M11[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)	1.3615	0.050426	27	0	0
M1	0.00849999999999968	0.067653	0.1256	0.900552	0.450276
M2	0.000499999999999861	0.067653	0.0074	0.994134	0.497067
M3	0.0254999999999998	0.067653	0.3769	0.707928	0.353964
M4	0.0374999999999998	0.067653	0.5543	0.582004	0.291002
M5	0.0168999999999998	0.067653	0.2498	0.803828	0.401914
M6	0.0124999999999998	0.067653	0.1848	0.854208	0.427104
M7	0.0220999999999998	0.067653	0.3267	0.745371	0.372686
M8	0.0160999999999998	0.067653	0.238	0.812933	0.406466
M9	0.0110999999999998	0.067653	0.1641	0.870378	0.435189
M10	0.0128999999999998	0.067653	0.1907	0.849599	0.4248
M11	-0.00770000000000014	0.067653	-0.1138	0.909869	0.454934

Multiple Linear Regression - Regression Statistics
Multiple R	0.128596492431053
R-squared	0.01653705786557
Adjusted R-squared	-0.213635120080786
F-TEST (value)	0.0718464673407405
F-TEST (DF numerator)	11
F-TEST (DF denominator)	47
p-value	0.999977091596499
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.100851671153571
Sum Squared Residuals	0.4780398

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	1.472	1.37	0.101999999999999
2	1.475	1.362	0.113
3	1.553	1.387	0.166
4	1.575	1.399	0.176
5	1.556	1.3784	0.1776
6	1.555	1.374	0.181
7	1.577	1.3836	0.1934
8	1.498	1.3776	0.1204
9	1.437	1.3726	0.0644000000000001
10	1.332	1.3744	-0.0423999999999999
11	1.273	1.3538	-0.0808000000000001
12	1.345	1.3615	-0.0165000000000001
13	1.324	1.37	-0.0459999999999998
14	1.279	1.362	-0.0830000000000001
15	1.305	1.387	-0.082
16	1.319	1.399	-0.08
17	1.365	1.3784	-0.0134
18	1.402	1.374	0.0279999999999999
19	1.409	1.3836	0.0254000000000001
20	1.427	1.3776	0.0494000000000001
21	1.456	1.3726	0.0834
22	1.482	1.3744	0.1076
23	1.491	1.3538	0.1372
24	1.461	1.3615	0.0994999999999999
25	1.427	1.37	0.0570000000000002
26	1.369	1.362	0.00699999999999999
27	1.357	1.387	-0.03
28	1.341	1.399	-0.058
29	1.257	1.3784	-0.1214
30	1.221	1.374	-0.153
31	1.277	1.3836	-0.1066
32	1.289	1.3776	-0.0886000000000001
33	1.307	1.3726	-0.0656
34	1.39	1.3744	0.0155999999999999
35	1.366	1.3538	0.0122000000000001
36	1.322	1.3615	-0.0395000000000001
37	1.336	1.37	-0.0339999999999997
38	1.365	1.362	0.00299999999999999
39	1.4	1.387	0.0129999999999999
40	1.444	1.399	0.045
41	1.435	1.3784	0.0566000000000001
42	1.439	1.374	0.0650000000000001
43	1.426	1.3836	0.0424
44	1.434	1.3776	0.0564
45	1.377	1.3726	0.00440000000000004
46	1.371	1.3744	-0.00339999999999993
47	1.356	1.3538	0.00220000000000009
48	1.318	1.3615	-0.0435000000000001
49	1.291	1.37	-0.0789999999999999
50	1.322	1.362	-0.04
51	1.32	1.387	-0.0669999999999999
52	1.316	1.399	-0.0829999999999999
53	1.279	1.3784	-0.0994000000000001
54	1.253	1.374	-0.121
55	1.229	1.3836	-0.1546
56	1.24	1.3776	-0.1376
57	1.286	1.3726	-0.0866
58	1.297	1.3744	-0.0774
59	1.283	1.3538	-0.0708000000000001

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
15	0.960599341492611	0.0788013170147775	0.0394006585073888
16	0.982396130507237	0.0352077389855255	0.0176038694927627
17	0.982295339742124	0.0354093205157521	0.0177046602578761
18	0.979674084752185	0.0406518304956308	0.0203259152478154
19	0.979055357019373	0.0418892859612544	0.0209446429806272
20	0.969924991842945	0.0601500163141106	0.0300750081570553
21	0.960899615210994	0.0782007695780121	0.0391003847890061
22	0.964731876455457	0.0705362470890868	0.0352681235445434
23	0.982188408669513	0.035623182660974	0.017811591330487
24	0.98353508292603	0.0329298341479406	0.0164649170739703
25	0.979125662618361	0.0417486747632775	0.0208743373816387
26	0.963817907194516	0.0723641856109673	0.0361820928054837
27	0.943962789413326	0.112074421173349	0.0560372105866743
28	0.925272829344044	0.149454341311912	0.0747271706559561
29	0.943530812770489	0.112938374459023	0.0564691872295115
30	0.971013609520657	0.0579727809586853	0.0289863904793426
31	0.970662254173476	0.0586754916530484	0.0293377458265242
32	0.963207944708578	0.0735841105828435	0.0367920552914218
33	0.946603102002686	0.106793795994627	0.0533968979973136
34	0.918091529346927	0.163816941306146	0.0819084706530729
35	0.875919060935303	0.248161878129393	0.124080939064697
36	0.817625023445511	0.364749953108978	0.182374976554489
37	0.747919320364108	0.504161359271783	0.252080679635892
38	0.655656762117374	0.688686475765253	0.344343237882626
39	0.566912991178248	0.866174017643503	0.433087008821752
40	0.512471357509572	0.975057284980857	0.487528642490428
41	0.492609846717375	0.985219693434751	0.507390153282625
42	0.533509983326878	0.932980033346245	0.466490016673122
43	0.636284225376526	0.727431549246948	0.363715774623474
44	0.827291895764986	0.345416208470028	0.172708104235014

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	7	0.233333333333333	NOK
10% type I error level	15	0.5	NOK