Multiple Linear Regression - Estimated Regression Equation
VerstrB[t] = + 29.4332755647748 + 0.779211994822692ExactB[t] -0.545825151595048VerstrV[t] + 0.289144634021937ExactV[t] + 0.599487261699369VerstrW[t] -0.110697882499544`ExactW `[t] -1.25157762149361t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)29.433275564774820.6374981.42620.1648650.082432
ExactB0.7792119948226920.1087997.161900
VerstrV-0.5458251515950480.376601-1.44930.158350.079175
ExactV0.2891446340219370.2656791.08830.2857310.142866
VerstrW0.5994872616993690.3239031.85080.0747710.037386
`ExactW `-0.1106978824995440.497498-0.22250.8255330.412766
t-1.251577621493610.756475-1.65450.1091970.054599


Multiple Linear Regression - Regression Statistics
Multiple R0.997955555922536
R-squared0.995915291596658
Adjusted R-squared0.995039996938799
F-TEST (value)1137.80574650457
F-TEST (DF numerator)6
F-TEST (DF denominator)28
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation32.7805214893154
Sum Squared Residuals30087.7524951212


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
12346.5208158444637-23.5208158444637
23965.1466072033872-26.1466072033872
394112.831083295647-18.8310832956468
4182179.3274778013952.67252219860542
5347321.78205478136125.2179452186395
6498471.03530687838526.9646931216148
7646604.78613414606241.2138658539377
8802752.34786745132249.6521325486775
9786826.027926940921-40.0279269409209
10875860.66636997562914.3336300243706
11985948.25314472128636.7468552787136
1210221060.03268192404-38.0326819240447
1310641095.84665010971-31.8466501097097
1411201181.26608599609-61.26608599609
1512701227.2534845930142.746515406991
1612851281.243144484633.75685551536991
1712711246.0805720676924.9194279323113
1812891232.9736751949856.0263248050189
1911971219.8603293523-22.8603293522984
2010861104.03976348552-18.0397634855201
219981023.51447699064-25.5144769906358
22842822.65493683685719.3450631631428
23742777.736785772197-35.7367857721969
24623627.467862451286-4.46786245128552
25514515.883412887007-1.88341288700717
26423406.94557521756216.0544247824378
27264314.981589669861-50.9815896698612
28158183.012905468876-25.0129054688759
2910587.67524476718917.324755232811
305970.9016124398013-11.9016124398013
314629.802902745454116.1970972545459
321612.14652702737413.85347297262585
33223.9232558305430918.0767441694569
343-1.711893162662924.71189316266292
355-11.256371189811816.2563711898118


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.001023980218150740.002047960436301480.998976019781849
110.659432462168350.68113507566330.34056753783165
120.6281988470863250.743602305827350.371801152913675
130.7076168611828220.5847662776343570.292383138817178
140.7527998260024890.4944003479950220.247200173997511
150.7523223128760980.4953553742478040.247677687123902
160.8249289962526870.3501420074946260.175071003747313
170.7889247418156520.4221505163686950.211075258184348
180.8227378761319490.3545242477361020.177262123868051
190.945997135547250.10800572890550.05400286445275
200.9168526560442080.1662946879115850.0831473439557925
210.9394380780254320.1211238439491360.0605619219745682
220.995484941122810.009030117754379390.0045150588771897
230.984492969097240.03101406180551940.0155070309027597
240.9748992964124580.05020140717508360.0251007035875418
250.9661899394065030.06762012118699360.0338100605934968


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level20.125NOK
5% type I error level30.1875NOK
10% type I error level50.3125NOK