Multiple Linear Regression - Estimated Regression Equation
pre[t] = + 0.143397173040697 + 0.366634435319895post1[t] -0.0239273405447953post2[t] -0.0458517852672986post3[t] + 0.138407579476121post4[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)0.1433971730406970.0921591.5560.1228740.061437
post10.3666344353198950.094933.86222e-041e-04
post2-0.02392734054479530.028669-0.83460.4059320.202966
post3-0.04585178526729860.105828-0.43330.6657550.332877
post40.1384075794761210.0594872.32670.0220.011


Multiple Linear Regression - Regression Statistics
Multiple R0.445518250634305
R-squared0.198486511648251
Adjusted R-squared0.166425972114181
F-TEST (value)6.19099099805618
F-TEST (DF numerator)4
F-TEST (DF denominator)100
p-value0.000171370633102019
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.457670396270712
Sum Squared Residuals20.946219162259


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
110.6911374051336530.308862594866347
210.7868467673128350.213153232687165
300.576081830128295-0.576081830128295
400.143397173040697-0.143397173040697
510.6025874025694150.397412597430585
610.7409949820455360.259005017954464
710.7409949820455360.259005017954464
800.602587402569415-0.602587402569415
900.645285619866355-0.645285619866355
1010.762919426768040.23708057323196
1100.324502969813758-0.324502969813758
1200.464179823093294-0.464179823093294
1300.416325142003703-0.416325142003703
1400.786846767312835-0.786846767312835
1500.143397173040697-0.143397173040697
1610.7409949820455360.259005017954464
1710.762919426768040.23708057323196
1810.5333836128313540.466616387168646
1900.740994982045536-0.740994982045536
2000.0496907066838079-0.0496907066838079
2110.6931403009559460.306859699044054
2210.4861042678157970.513895732184203
2300.0955424919511064-0.0955424919511064
2410.1433971730406970.856602826959303
2510.669212960411150.33078703958885
2610.09754538777339840.902454612226602
2710.5100316083605920.489968391639408
2800.143397173040697-0.143397173040697
2900.396284991448144-0.396284991448144
3010.6025874025694150.397412597430585
3110.2126009627787580.787399037221242
3210.6911374051336540.308862594866346
3300.166749177511459-0.166749177511459
3400.119469832495902-0.119469832495902
3500.166749177511459-0.166749177511459
3610.5100316083605920.489968391639408
3710.6911374051336540.308862594866346
3800.440252482548499-0.440252482548499
3900.602587402569415-0.602587402569415
4010.6452856198663550.354714380133645
4110.6025874025694150.397412597430585
4210.6452856198663550.354714380133645
4310.5100316083605920.489968391639408
4410.5333836128313540.466616387168646
4500.0975453877733984-0.0975453877733984
4600.645285619866355-0.645285619866355
4700.510031608360592-0.510031608360592
4810.6484391878367140.351560812163286
4910.6452856198663550.354714380133645
5000.116891600599577-0.116891600599577
5100.740994982045536-0.740994982045536
5210.7170676415007410.282932358499259
5300.740994982045536-0.740994982045536
5400.0476878108615159-0.0476878108615159
5500.510031608360592-0.510031608360592
5600.416325142003703-0.416325142003703
5700.533383612831355-0.533383612831355
5800.414322246181411-0.414322246181411
5900.324502969813758-0.324502969813758
6000.143397173040697-0.143397173040697
6100.464179823093294-0.464179823093294
6210.6452856198663550.354714380133645
6310.6025874025694150.397412597430585
6410.09754538777339840.902454612226602
6500.32650586563605-0.32650586563605
6600.648439187836714-0.648439187836714
6700.740994982045536-0.740994982045536
6800.143397173040697-0.143397173040697
6910.5068780403902340.493121959609766
7010.6452856198663550.354714380133645
7100.462176927271002-0.462176927271002
7200.510031608360592-0.510031608360592
7300.510031608360592-0.510031608360592
7400.414322246181411-0.414322246181411
7510.7409949820455360.259005017954464
7610.3743605467256410.625639453274359
7700.350433206180846-0.350433206180846
7810.6931403009559460.306859699044054
7910.3743605467256410.625639453274359
8010.6931403009559460.306859699044054
8100.374360546725641-0.374360546725641
8200.27865118454646-0.27865118454646
8300.27865118454646-0.27865118454646
8410.3743605467256410.625639453274359
8500.143397173040697-0.143397173040697
8600.27865118454646-0.27865118454646
8710.1433971730406970.856602826959303
8810.6452856198663550.354714380133645
8900.32650586563605-0.32650586563605
9000.0955424919511064-0.0955424919511064
9110.5100316083605920.489968391639408
9210.7409949820455360.259005017954464
9310.4143222461814110.585677753818589
9400.740994982045536-0.740994982045536
9510.7409949820455360.259005017954464
9610.7409949820455360.259005017954464
9710.6452856198663550.354714380133645
9810.6452856198663550.354714380133645
9900.143397173040697-0.143397173040697
10000.143397173040697-0.143397173040697
10110.4621769272710020.537823072728998
10200.350433206180846-0.350433206180846
10300.143397173040697-0.143397173040697
10400.32650586563605-0.32650586563605
10500.486104267815797-0.486104267815797


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.6235075567387810.7529848865224390.376492443261219
90.5518954733581550.896209053283690.448104526641845
100.4165334956902470.8330669913804930.583466504309754
110.2940743990731920.5881487981463830.705925600926808
120.2071615467459360.4143230934918730.792838453254064
130.1476385876649650.2952771753299290.852361412335035
140.5750424169772520.8499151660454960.424957583022748
150.4787008587692010.9574017175384010.521299141230799
160.4076274769335810.8152549538671620.592372523066419
170.338467741630080.676935483260160.66153225836992
180.4061636033479910.8123272066959830.593836396652009
190.5463131250267860.9073737499464280.453686874973214
200.500344730681050.9993105386378990.49965526931895
210.4882788720246080.9765577440492160.511721127975392
220.5057322758121280.9885354483757440.494267724187872
230.4309332015850020.8618664031700040.569066798414998
240.5787193683687220.8425612632625560.421280631631278
250.5905767602676410.8188464794647170.409423239732359
260.7315196631367480.5369606737265040.268480336863252
270.7131017040162160.5737965919675680.286898295983784
280.6814652271694930.6370695456610140.318534772830507
290.6626539384462770.6746921231074460.337346061553723
300.6353673681067650.7292652637864690.364632631893235
310.7072398442687430.5855203114625140.292760155731257
320.6912110092488770.6175779815022470.308788990751123
330.6424507757189870.7150984485620260.357549224281013
340.5957422581109280.8085154837781430.404257741889072
350.540617442957020.918765114085960.45938255704298
360.5182260935312190.9635478129375620.481773906468781
370.4898942711663910.9797885423327820.510105728833609
380.5029959217219630.9940081565560750.497004078278037
390.5519853904085160.8960292191829680.448014609591484
400.5513104266355520.8973791467288950.448689573364448
410.5317889974640910.9364220050718190.468211002535909
420.5187458496090060.9625083007819880.481254150390994
430.5125004152038080.9749991695923850.487499584796192
440.502815570488380.9943688590232390.49718442951162
450.447863416563730.8957268331274590.55213658343627
460.4918414164146970.9836828328293930.508158583585303
470.5415953308685840.9168093382628310.458404669131416
480.5315201079790860.9369597840418280.468479892020914
490.5154692319565880.9690615360868240.484530768043412
500.4605029430157340.9210058860314680.539497056984266
510.5367053414078920.9265893171842160.463294658592108
520.5074356504722460.9851286990555080.492564349527754
530.5806067201743010.8387865596513970.419393279825699
540.5258185111072750.948362977785450.474181488892725
550.5498547099276270.9002905801447450.450145290072373
560.5666997081498310.8666005837003370.433300291850169
570.6261299129114720.7477401741770570.373870087088528
580.618747093731730.762505812536540.38125290626827
590.5751587369619840.8496825260760320.424841263038016
600.5223055708924830.9553888582150340.477694429107517
610.695560499575860.6088790008482790.30443950042414
620.6767721212764050.646455757447190.323227878723595
630.6438492421427180.7123015157145650.356150757857282
640.670898681007010.6582026379859790.32910131899299
650.6407418686331850.7185162627336310.359258131366815
660.6317444736261510.7365110527476980.368255526373849
670.7438022534346440.5123954931307110.256197746565356
680.6949489385564040.6101021228871910.305051061443596
690.6620077810421530.6759844379156930.337992218957847
700.6294587798048310.7410824403903370.370541220195169
710.6337663205695810.7324673588608380.366233679430419
720.6698101898859780.6603796202280450.330189810114022
730.7294577776196320.5410844447607360.270542222380368
740.7527264397757120.4945471204485760.247273560224288
750.7025651449581450.5948697100837090.297434855041855
760.7716342507047960.4567314985904070.228365749295204
770.7412795879724270.5174408240551460.258720412027573
780.6920180051129390.6159639897741210.307981994887061
790.7919438644447540.4161122711104930.208056135555246
800.7471613368666780.5056773262666440.252838663133322
810.7064398642983260.5871202714033480.293560135701674
820.65269989575010.69460020849980.3473001042499
830.5974650734875410.8050698530249170.402534926512459
840.7711505218916420.4576989562167160.228849478108358
850.7079735203525190.5840529592949620.292026479647481
860.6486860502419120.7026278995161760.351313949758088
870.9054865149859650.1890269700280690.0945134850140345
880.8639621053052090.2720757893895820.136037894694791
890.8107283316351710.3785433367296580.189271668364829
900.736979514385250.52604097122950.26302048561475
910.7165589720113240.5668820559773510.283441027988676
920.6831917279668730.6336165440662550.316808272033127
930.5962250198185220.8075499603629550.403774980181478
940.8106083817377830.3787832365244330.189391618262217
950.7148170690517420.5703658618965160.285182930948258
960.8855647357890110.2288705284219790.114435264210989
970.7645376605341110.4709246789317790.235462339465889


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level00OK