Multiple Linear Regression - Estimated Regression Equation
aardolie[t] = + 107.295886085488 -357.330033784989datum[t] + 0.180840125155705steenkool[t] -0.494748190846368uranium[t] + 0.479696472235983metaal[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)107.2958860854883.19108933.623600
datum-357.330033784989259.090173-1.37920.1722320.086116
steenkool0.1808401251557050.3444390.5250.6012230.300612
uranium-0.4947481908463680.363656-1.36050.1780420.089021
metaal0.4796964722359830.3383691.41770.1607230.080361


Multiple Linear Regression - Regression Statistics
Multiple R0.284916769239512
R-squared0.0811775653938812
Adjusted R-squared0.0286734262735315
F-TEST (value)1.54611744433723
F-TEST (DF numerator)4
F-TEST (DF denominator)70
p-value0.198414892624847
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation8.71199939334221
Sum Squared Residuals5312.92534007165


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1100104.204902426588-4.20490242658802
299109.276450052977-10.2764500529775
3108106.1802624432741.81973755672616
4103109.324746964013-6.32474696401317
599105.771655286549-6.77165528654876
6115111.3902251764323.60977482356833
790104.655900512372-14.6559005123716
895107.735701054725-12.7357010547246
9114107.0032945672856.99670543271512
10108111.698738728833-3.69873872883259
11112106.7271542632135.27284573678722
12109108.322347393910.67765260608984
13105103.2129261266551.78707387334462
14105107.027331155806-2.02733115580585
15118107.72323440974210.2767655902575
16103106.640728771439-3.64072877143858
17112106.3046893270215.69531067297853
18116107.3999633996738.60003660032715
1996107.140072077943-11.1400720779428
20101103.057096821707-2.05709682170676
21116107.5938832713888.40611672861226
22119110.4809054512978.51909454870266
23115108.8571260141826.14287398581819
24108105.3213672944332.67863270556679
25111103.1404189284097.8595810715906
26108102.8269241660445.1730758339557
27121107.26212381650813.7378761834916
28109107.0104948158561.98950518414362
29112109.5826222610032.41737773899657
30119107.63643961687811.3635603831222
31104109.315349741495-5.31534974149525
32105107.402195404613-2.40219540461253
33115109.5253996990565.47460030094368
34124107.45226506942716.5477349305729
35116106.2730310302929.72696896970783
36107105.3215965773341.6784034226663
37115100.55642496237414.443575037626
38116106.6118786626449.38812133735576
39116109.2570845166296.74291548337142
40119110.8210256805088.17897431949232
41111102.400379099998.59962090000986
42118108.4230673520829.57693264791779
43106103.0144668371482.98553316285176
44103109.462024400426-6.46202440042573
45118105.18094059473512.8190594052651
46118106.94535705419711.0546429458028
47102103.575934139132-1.57593413913223
48100104.88990134425-4.88990134424954
4994100.207527792957-6.20752779295688
5094104.132810033223-10.1328100332235
51102105.503326273707-3.5033262737071
5295106.097586359249-11.097586359249
5392107.564587812016-15.5645878120159
54102108.046778273166-6.04677827316558
5591108.477374986652-17.4773749866524
5689106.232545719315-17.2325457193147
57104110.455280020545-6.45528002054461
58105106.415545960354-1.41554596035411
5999107.951033811274-8.95103381127448
6095105.628542389985-10.6285423899854
6190103.691177062057-13.6911770620567
6296109.116868294579-13.1168682945792
63113108.7615489982624.23845100173827
64101102.775712222375-1.77571222237498
65101109.436150153494-8.43615015349413
66113108.5419689133314.45803108666945
6796104.861175817686-8.86117581768552
6897104.331771475993-7.33177147599266
69114106.567833497297.43216650271012
70112106.6695214701815.33047852981924
71108110.053518190156-2.05351819015567
72107107.379151442409-0.379151442409042
73103103.811933741576-0.811933741575802
74107102.5153569754624.4846430245377
75122108.8353235502213.16467644978


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.4376492531280760.8752985062561520.562350746871924
90.3370847747062530.6741695494125070.662915225293747
100.2160451618426250.432090323685250.783954838157375
110.3711916551327760.7423833102655510.628808344867224
120.2967844603157180.5935689206314360.703215539684282
130.2173152146424260.4346304292848510.782684785357574
140.1478112160222520.2956224320445050.852188783977748
150.2710759430629390.5421518861258790.728924056937061
160.1997953265934330.3995906531868650.800204673406567
170.2235499280152660.4470998560305320.776450071984734
180.2590344201634010.5180688403268020.740965579836599
190.3026455711863960.6052911423727920.697354428813604
200.2322789002830640.4645578005661290.767721099716936
210.2516121752492890.5032243504985790.748387824750711
220.2422367066875250.484473413375050.757763293312475
230.2149659229802290.4299318459604580.785034077019771
240.162442889665820.324885779331640.83755711033418
250.1654323158876810.3308646317753620.834567684112319
260.1398045981789790.2796091963579590.86019540182102
270.2410716595285050.482143319057010.758928340471495
280.1878854144640150.3757708289280310.812114585535985
290.1437372835861570.2874745671723150.856262716413843
300.1562440512386490.3124881024772980.843755948761351
310.1379765584822570.2759531169645150.862023441517743
320.1084399017821190.2168798035642380.891560098217881
330.08735406845803990.174708136916080.91264593154196
340.1744258210701380.3488516421402750.825574178929862
350.1751077318648310.3502154637296630.824892268135169
360.1397973915389590.2795947830779190.860202608461041
370.2231427201207080.4462854402414160.776857279879292
380.250769004093550.50153800818710.74923099590645
390.2439969534058450.487993906811690.756003046594155
400.257628714082510.5152574281650210.74237128591749
410.2446416711487740.4892833422975480.755358328851226
420.284094342586360.568188685172720.71590565741364
430.2317249437479480.4634498874958970.768275056252052
440.2039231680043890.4078463360087790.796076831995611
450.3508256138510790.7016512277021580.649174386148921
460.5011609037818960.9976781924362070.498839096218103
470.4570957523410920.9141915046821840.542904247658908
480.411280990246960.822561980493920.58871900975304
490.3783767004430350.7567534008860710.621623299556965
500.3851181204837620.7702362409675230.614881879516238
510.3287128893224390.6574257786448790.671287110677561
520.3660515141223660.7321030282447320.633948485877634
530.4196373697808950.8392747395617890.580362630219105
540.3554824722023630.7109649444047260.644517527797637
550.5066193724971350.9867612550057310.493380627502865
560.7642594772655420.4714810454689160.235740522734458
570.7221776957208540.5556446085582920.277822304279146
580.6403537786339720.7192924427320560.359646221366028
590.6895487887797950.620902422440410.310451211220205
600.6422767845136140.7154464309727710.357723215486386
610.6864529358886580.6270941282226850.313547064111342
620.7355611394160260.5288777211679470.264438860583974
630.6505779040618960.6988441918762080.349422095938104
640.5951902574287710.8096194851424580.404809742571229
650.6717639346083860.6564721307832290.328236065391614
660.6607977556940960.6784044886118090.339202244305904
670.646573517391090.706852965217820.35342648260891


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