Multiple Linear Regression - Estimated Regression Equation
wn[t] = -0.418850835801199 -0.00225081430349453ta[t] + 0.000353090163285318omzet[t] + 0.0160241336628865mw[t] -0.107337318460469winst[t] + 0.0363906856461829cf[t] + 3.96985998339162dienst[t] -2.35771541331388product[t] + 0.000855437130039981ta_d[t] + 0.00974096942632612omzet_d[t] -0.0117758455576938mw_d[t] + 0.267164326757753winst_d[t] -0.115761102660768cf_d[t] -0.000880137267368733ta_p[t] + 0.0153333181085418omzet_p[t] -0.0216815834484814mw_p[t] + 0.13504041258139winst_p[t] -0.0209937936157664cf_p[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-0.4188508358011994.828696-0.08670.9311610.46558
ta-0.002250814303494530.002955-0.76160.4492150.224608
omzet0.0003530901632853180.0035090.10060.9201780.460089
mw0.01602413366288650.0049043.26790.0017820.000891
winst-0.1073373184604690.075926-1.41370.1625310.081265
cf0.03639068564618290.0627610.57980.5641630.282082
dienst3.969859983391625.6992320.69660.4887240.244362
product-2.357715413313886.846833-0.34440.7317660.365883
ta_d0.0008554371300399810.0029710.28790.7743820.387191
omzet_d0.009740969426326120.0035972.70830.0087640.004382
mw_d-0.01177584555769380.005908-1.99310.0507250.025363
winst_d0.2671643267577530.0828183.22590.002020.00101
cf_d-0.1157611026607680.066855-1.73150.0884110.044205
ta_p-0.0008801372673687330.003656-0.24070.810570.405285
omzet_p0.01533331810854180.0040523.78370.0003550.000177
mw_p-0.02168158344848140.005493-3.94740.0002070.000104
winst_p0.135040412581390.0914181.47720.1447750.072387
cf_p-0.02099379361576640.084011-0.24990.803510.401755


Multiple Linear Regression - Regression Statistics
Multiple R0.983604735621981
R-squared0.967478275937988
Adjusted R-squared0.958414844642017
F-TEST (value)106.745254015231
F-TEST (DF numerator)17
F-TEST (DF denominator)61
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation13.1539797625996
Sum Squared Residuals10554.6581992877


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
118.221.6568545438032-3.45685454380321
2143.8137.1342028390136.66579716098685
323.424.5499156286502-1.14991562865021
41.12.89603040001339-1.79603040001339
549.567.9700692903106-18.4700692903106
64.817.6214065223235-12.8214065223235
720.819.4133428375471.38665716245305
819.45.949309782870813.4506902171292
92.15.14979696402705-3.04979696402705
1079.482.9717620430496-3.57176204304957
112.815.5320953176455-12.7320953176455
123.82.022021029210231.77797897078977
134.14.27884690996464-0.178846909964642
1413.214.1486635047642-0.948663504764192
152.84.0038037858585-1.20380378585851
1648.559.0564749163737-10.5564749163737
176.20.8789440224198925.32105597758011
1810.829.9263017662835-19.1263017662835
193.812.0082101754515-8.20821017545146
2021.922.7617239661268-0.861723966126758
2112.69.787170617896462.81282938210354
22128114.18075961372713.8192403862728
2387.363.537364308826823.7626356911732
241625.3678286439466-9.36782864394663
250.713.7354295863332-13.0354295863332
2622.510.716053401716111.7839465982839
2715.46.193174229919849.20682577008016
2835.3456848916174-2.34568489161739
292.14.89801464674306-2.79801464674306
304.14.59699492966701-0.496994929667014
316.49.79262484176468-3.39262484176468
3226.633.5546153109106-6.95461531091064
33304290.04541278951713.9545872104826
3418.630.4141210432007-11.8141210432007
356569.9319369626831-4.93193696268311
3666.247.234219706338618.9657802936614
378354.252802875825428.7471971241746
386253.56822760983998.43177239016013
391.64.14348689606351-2.54348689606351
40400.2409.849502963537-9.64950296353657
4123.33.633204625638219.6667953743618
424.62.846455385430641.75354461456936
43164.6177.365482455016-12.7654824550164
441.911.7544329818287-9.85443298182874
4557.573.2607010365384-15.7607010365384
462.44.33938797503698-1.93938797503698
4777.370.3124897393746.98751026062598
4815.88.119356077597197.68064392240282
490.6-7.138641620034157.73864162003415
503.50.5796147775875922.92038522241241
5199.12255633276976-0.122556332769764
526247.766632139656514.2333678603435
537.49.51450669372579-2.11450669372579
5415.67.136065745144698.46393425485531
5525.242.9237590165683-17.7237590165683
5625.427.0974797046171-1.69747970461711
573.52.980668519240640.519331480759363
5827.325.956027470581.34397252942004
5937.551.9255723456576-14.4255723456576
603.42.927174091828580.472825908171421
6114.320.2890446520356-5.9890446520356
626.114.4975226508702-8.39752265087017
634.97.83841282420111-2.93841282420111
643.311.9548980636366-8.65489806363658
6574.403166725991462.59683327400854
668.29.46268943677433-1.26268943677433
6743.538.69067265249444.80932734750565
6848.557.1892260418941-8.6892260418941
695.44.791955590158960.608044409841041
7049.554.892181804548-5.39218180454801
7129.15.8120550392053223.2879449607947
722.628.5491842210118-25.9491842210118
730.81.5717019656024-0.7717019656024
74184.8188.616629624554-3.81662962455432
752.31.434867316429330.865132683570666
76819.1831782691536-11.1831782691536
7710.315.0205683813587-4.72056838135867
785028.758120264214121.2418797357859
79118.173.745796866281944.3542031337181


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
210.4039645410181350.807929082036270.596035458981865
220.5930966168166440.8138067663667120.406903383183356
230.4863456445671290.9726912891342590.513654355432871
240.3700677878243020.7401355756486050.629932212175698
250.3468733444117420.6937466888234840.653126655588258
260.2547697748695350.5095395497390710.745230225130465
270.1885581143674960.3771162287349930.811441885632504
280.1216574328142630.2433148656285250.878342567185737
290.07914967476780730.1582993495356150.920850325232193
300.04708059031939170.09416118063878340.952919409680608
310.02791616003734960.05583232007469920.97208383996265
320.01533401391590650.03066802783181290.984665986084094
330.02608667070664990.05217334141329980.97391332929335
340.01702650274172960.03405300548345920.98297349725827
350.01286694779380660.02573389558761330.987133052206193
360.01793020548110580.03586041096221160.982069794518894
370.04927411221800040.09854822443600080.950725887782
380.03639979871327340.07279959742654680.963600201286727
390.02416464256633310.04832928513266630.975835357433667
400.06904152493090830.1380830498618170.930958475069092
410.1882216637509180.3764433275018360.811778336249082
420.1357019133535230.2714038267070450.864298086646477
430.3168546100908510.6337092201817020.683145389909149
440.3177054110072950.6354108220145890.682294588992705
450.6643446883834840.6713106232330320.335655311616516
460.5862907999740370.8274184000519250.413709200025963
470.6005832067690310.7988335864619380.399416793230969
480.58566683492960.8286663301408010.4143331650704
490.5147943408487740.9704113183024520.485205659151226
500.4174770679832190.8349541359664370.582522932016781
510.3215762960824730.6431525921649460.678423703917527
520.2429243910622470.4858487821244930.757075608937753
530.1760061723617740.3520123447235480.823993827638226
540.1317589687611470.2635179375222950.868241031238853
550.09461809354985760.1892361870997150.905381906450142
560.107280469839460.2145609396789190.89271953016054
570.0572304589944430.1144609179888860.942769541005557
580.02594876870104770.05189753740209530.974051231298952


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level50.131578947368421NOK
10% type I error level110.289473684210526NOK