Multiple Linear Regression - Estimated Regression Equation
Waalsm[t] = -130.339838114327 + 0.034984131069266Vlaamsm[t] -0.206430397593295Vlaamsvr[t] + 1.33218483391395Waalsvr[t] + 0.334891195292699Brusselm[t] -0.352391285465773Brusselvr[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-130.33983811432794.597577-1.37780.1752220.087611
Vlaamsm0.0349841310692660.1275840.27420.7852110.392605
Vlaamsvr-0.2064303975932950.114762-1.79880.0789180.039459
Waalsvr1.332184833913950.07181618.549900
Brusselm0.3348911952926990.2369571.41330.1646040.082302
Brusselvr-0.3523912854657730.211367-1.66720.1025780.051289


Multiple Linear Regression - Regression Statistics
Multiple R0.99873293121104
R-squared0.997467467885395
Adjusted R-squared0.997179680145099
F-TEST (value)3465.98318211721
F-TEST (DF numerator)5
F-TEST (DF denominator)44
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.63857676401103
Sum Squared Residuals306.331842941472


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
115121514.61987017451-2.61987017450808
215171516.494166702480.505833297520852
315251522.53794536412.4620546358996
415401533.791469217546.20853078245799
515471542.213736184124.78626381588153
615471544.79142760082.20857239919528
715471547.60105084301-0.601050843012691
815471547.57129007888-0.571290078876164
915461548.82472036551-2.82472036551043
1015331533.97386527973-0.973865279728585
1115381537.901147937330.0988520626684176
1215431542.479247579240.520752420761695
1315491548.767408719180.232591280823706
1415561556.97357521868-0.973575218678098
1515591561.34511868127-2.34511868126749
1615591562.40603453921-3.40603453921207
1715631567.73991960791-4.73991960790721
1815631567.02279872912-4.02279872911882
1915641568.06621449689-4.06621449689033
2015641567.52052383535-3.52052383534908
2115571561.04068651572-4.04068651572201
2215541557.1762090315-3.17620903150279
2315521552.17649440782-0.176494407822091
2415521551.284294993410.715705006590435
2515511549.56624820691.43375179310018
2615521547.95315381364.04684618640213
2715541549.923753126854.07624687314883
2815671564.368452149762.63154785023535
2915721568.206675357223.7933246427766
3015791577.52108015361.4789198464041
3115881586.518109894131.48189010587435
3215971594.956285853042.04371414695742
3316031601.415877210231.58412278977228
3416071605.999843335451.00015666454794
3516071607.01626026063-0.0162602606327763
3616091609.58075907118-0.580759071184693
3716121612.80555756918-0.805557569181171
3816151615.58448811508-0.584488115081739
3916191620.12397135682-1.12397135681909
4016221623.1503247457-1.15032474570075
4116281629.64136164803-1.64136164802533
4216341635.57496454951-1.57496454950602
4316401639.557712814790.442287185208588
4416481648.06235054847-0.0623505484707959
4516571656.825996584160.174003415843905
4616681668.83981676404-0.839816764042268
4716781678.26733055916-0.267330559164706
4816871688.8380828315-1.83808283150399
4917001697.180834635692.81916536430642
5017141710.201492741963.79850725804165


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.3682156457347270.7364312914694540.631784354265273
100.3030028463354390.6060056926708780.696997153664561
110.1939501932053030.3879003864106060.806049806794697
120.1636525230575570.3273050461151150.836347476942443
130.1610937641572180.3221875283144370.838906235842781
140.572705039282450.8545899214351010.42729496071755
150.8642373466884170.2715253066231650.135762653311583
160.82400429341660.35199141316680.1759957065834
170.7497665429663460.5004669140673090.250233457033654
180.7740211657853980.4519576684292030.225978834214602
190.8749821714816060.2500356570367880.125017828518394
200.9313953906758840.1372092186482330.0686046093241163
210.9451518302298760.1096963395402490.0548481697701244
220.9589243547131480.08215129057370340.0410756452868517
230.9798284837759350.04034303244812990.0201715162240649
240.992130497356110.01573900528778090.00786950264389047
250.9977693927727860.004461214454427810.00223060722721391
260.9965204203719040.006959159256192110.00347957962809605
270.9942045531679680.01159089366406320.0057954468320316
280.9966848086597260.006630382680548410.00331519134027421
290.9979114909349230.004177018130153410.0020885090650767
300.9987091484018580.002581703196283290.00129085159814164
310.9994827581779230.001034483644154790.000517241822077394
320.9995273914621970.0009452170756058140.000472608537802907
330.9989816762446760.002036647510648840.00101832375532442
340.998492825309450.003014349381099490.00150717469054974
350.9968325626558470.006334874688305180.00316743734415259
360.9918653459274720.01626930814505570.00813465407252785
370.9799994965570870.04000100688582580.0200005034429129
380.9670314603227360.06593707935452870.0329685396772644
390.9785535249743930.04289295005121410.021446475025607
400.9708568156487350.05828636870252910.0291431843512646
410.9175891971145310.1648216057709380.0824108028854691


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.303030303030303NOK
5% type I error level160.484848484848485NOK
10% type I error level190.575757575757576NOK