Multiple Linear Regression - Estimated Regression Equation
Y[t] = -3.41688587976048 + 1.20546558206975X[t] + 0.734699728850762M1[t] -0.399983124851524M2[t] -1.07941969149607M3[t] -1.30156881538096M4[t] + 0.918927117380584M5[t] -1.14382590744882M6[t] -1.12257083876042M7[t] -0.918252357196105M8[t] -0.795192302966259M9[t] -0.822570838760416M10[t] -0.501366395517438M11[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-3.416885879760480.530798-6.437300
X1.205465582069750.02839342.456700
M10.7346997288507620.3019442.43320.0180140.009007
M2-0.3999831248515240.303831-1.31650.1931090.096554
M3-1.079419691496070.309045-3.49280.0009130.000456
M4-1.301568815380960.307785-4.22888.3e-054.1e-05
M50.9189271173805840.3054023.00890.0038520.001926
M6-1.143825907448820.302514-3.78110.0003670.000183
M7-1.122570838760420.308844-3.63480.0005850.000293
M8-0.9182523571961050.30294-3.03110.0036150.001807
M9-0.7951923029662590.303063-2.62380.011050.005525
M10-0.8225708387604160.308844-2.66340.0099570.004978
M11-0.5013663955174380.301944-1.66050.1021280.051064


Multiple Linear Regression - Regression Statistics
Multiple R0.985670635867928
R-squared0.971546602412285
Adjusted R-squared0.96575947069953
F-TEST (value)167.880506377776
F-TEST (DF numerator)12
F-TEST (DF denominator)59
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.522837820203883
Sum Squared Residuals16.1282037878973


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
11817.08744939503420.912550604965844
219.617.64041835622951.95958164377053
323.322.38557690889880.914423091101224
423.722.76616057604880.93383942395124
520.319.56206138949640.73793861050355
622.822.4417172511530.358282748847004
724.324.2711706929460.0288293070539764
821.521.3412786611290.158721338871001
923.523.5136302048774-0.0136302048774122
1022.221.55750673777170.642493262228339
1120.921.6376180646007-0.737618064600691
1222.221.77734478549720.422655214502796
1319.518.89564776813870.604352231861272
1421.121.1362685442317-0.0362685442317284
152222.2650303506918-0.2650303506918
1619.219.14976382983950.0502361701604758
1717.818.8387820402546-1.03878204025460
1819.219.06641362135770.133586378642285
1919.920.5342273885298-0.634227388529817
2019.619.53308028802440.066919711975621
2118.118.2095816437705-0.109581643770531
2220.421.0753205049438-0.675320504943764
2318.118.5034075512194-0.403407551219352
2418.619.3664136213577-0.766413621357711
2517.618.1723684188969-0.572368418896882
2619.420.2924426367829-0.892442636782911
2719.319.4924595119314-0.192459511931384
2818.618.7881241552186-0.188124155218597
2916.917.03058366715-0.130583667149985
3016.416.6554824572182-0.255482457218225
311919.3287618064601-0.328761806460069
3218.719.0508940551965-0.35089405519648
3317.116.52192982887290.578070171127115
3421.521.19586706315070.304132936849261
3517.817.53903508556360.260964914436444
3618.117.67876180646010.421238193539931
371919.0161943263457-0.0161943263457042
3818.919.2075236129201-0.307523612920141
3916.816.8404352313779-0.0404352313779446
4018.118.4264844805977-0.326484480597673
4115.715.7045715268733-0.00457152687326499
4215.115.08837720052760.0116227994724468
4318.317.88220310797640.417796892023625
4416.516.39886977464300.101130225356960
4516.917.2452091781147-0.345209178114737
4618.418.7849358990112-0.384935899011249
4716.416.09247638707990.307523612920135
4815.715.8705634333555-0.170563433355452
4916.917.4490890696550-0.549089069655036
5016.617.1582321234016-0.558232123401568
5116.717.0815283477919-0.381528347791894
5216.616.7388326657000-0.138832665700031
5314.414.25801282838960.141987171610430
5414.514.6061909676997-0.106190967699654
5517.517.03837720052750.461622799472449
5614.314.22903172691750.0709682730825013
5715.415.5575573632171-0.157557363217089
5817.217.3383772005275-0.138377200527550
5914.614.52537113038920.074628869610807
6014.214.18291161845780.0170883815421924
6114.915.2792510219295-0.379251021929493
6214.114.2651147264342-0.165114726434182
6315.615.6349696493082-0.0349696493082004
6414.614.9306342925954-0.330634292595414
6511.911.60598854783610.294011452163872
6613.513.6418185020439-0.141818502043857
6714.214.14525980356020.0547401964398365
6813.713.7468454940896-0.0468454940896024
6914.414.35209178114730.0479082188526546
7015.315.04799259459500.252007405404966
7114.313.80209178114730.497908218852657
7214.514.42400473487180.0759952651282423


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
160.9999430811569980.0001138376860047425.69188430023711e-05
170.999999518653739.62692539743804e-074.81346269871902e-07
180.9999992235673871.55286522666963e-067.76432613334816e-07
190.9999994040131881.19197362386398e-065.95986811931988e-07
200.999998526665962.94666808025999e-061.47333404013000e-06
210.9999953169994549.36600109286098e-064.68300054643049e-06
220.9999988553927272.28921454524931e-061.14460727262465e-06
230.9999988075954692.3848090628943e-061.19240453144715e-06
240.9999998367622933.26475414824186e-071.63237707412093e-07
250.9999999424823991.15035201905097e-075.75176009525486e-08
260.9999999971623995.67520310122625e-092.83760155061313e-09
270.9999999913010391.73979217390166e-088.69896086950832e-09
280.9999999785615834.28768334043395e-082.14384167021698e-08
290.999999940459891.19080220746376e-075.9540110373188e-08
300.9999998338460733.32307854473301e-071.66153927236650e-07
310.9999999027797031.94440594027424e-079.72202970137118e-08
320.9999998750634282.49873143519910e-071.24936571759955e-07
330.9999999878653842.42692319722496e-081.21346159861248e-08
340.9999999871706232.56587533799543e-081.28293766899771e-08
350.9999999703207035.93585949494231e-082.96792974747115e-08
360.9999999874330612.51338776630236e-081.25669388315118e-08
370.9999999961052427.78951557615589e-093.89475778807795e-09
380.9999999918422761.63154479881632e-088.15772399408162e-09
390.999999976815984.6368038952554e-082.3184019476277e-08
400.9999999227646271.54470746348536e-077.7235373174268e-08
410.999999719006055.61987899112769e-072.80993949556384e-07
420.9999992109536661.57809266894906e-067.89046334474532e-07
430.9999988940407552.21191849070622e-061.10595924535311e-06
440.9999977180781464.56384370714652e-062.28192185357326e-06
450.99999324029511.35194098008716e-056.75970490043579e-06
460.9999887203401742.25593196512221e-051.12796598256111e-05
470.9999679401024446.41197951114319e-053.20598975557160e-05
480.9999020851885970.0001958296228056879.79148114028435e-05
490.999720888108020.0005582237839618120.000279111891980906
500.9994700318931280.001059936213744170.000529968106872087
510.9990454119112420.001909176177516020.00095458808875801
520.9975617181214140.004876563757171220.00243828187858561
530.9926343964208180.01473120715836340.00736560357918168
540.9780094447555880.04398111048882390.0219905552444119
550.9954989629676950.009002074064610860.00450103703230543
560.987239928878320.02552014224335870.0127600711216793


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level380.926829268292683NOK
5% type I error level411NOK
10% type I error level411NOK