Multiple Linear Regression - Estimated Regression Equation
bewegingen[t] = + 8650.42436770292 + 0.00580420016496377passagiers[t] + 0.0857171609177784cargo[t] -0.00293593909601016auto[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)8650.42436770292759.80038311.385100
passagiers0.005804200164963770.0009436.156500
cargo0.08571716091777840.0094019.117800
auto-0.002935939096010160.006804-0.43150.6674540.333727


Multiple Linear Regression - Regression Statistics
Multiple R0.899279511857937
R-squared0.808703640447449
Adjusted R-squared0.800264095173072
F-TEST (value)95.8231295829055
F-TEST (DF numerator)3
F-TEST (DF denominator)68
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation831.41292487375
Sum Squared Residuals47004826.7120045


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
11891917782.74098196611136.25901803386
21914718425.5537723079721.446227692107
32151819932.55624606651585.44375393354
42094120592.5021524865348.497847513514
52240121200.70804843801200.29195156204
62218121017.14702443451163.85297556553
72249422573.6313708935-79.6313708935403
82147921803.2336143818-324.233614381789
92232221759.9588920445562.0411079555
102182920835.5746687345993.425331265515
112037019857.3223676994512.677632300595
121846719002.0287899932-535.028789993215
131878018621.2126612955158.787338704461
141881518832.6225748896-17.6225748896364
152088120603.8555974171277.144402582912
162144321294.2248372602148.77516273981
172233321403.1705134291929.829486570876
182294421720.26637161381223.73362838624
192253623155.5457661379-619.545766137909
202165821922.5769183946-264.576918394605
212303522421.5780552314613.421944768598
222196921587.8447699248381.155230075214
232029720238.463840297658.5361597024423
241856419508.4944602152-944.494460215215
251884418855.4464284892-11.4464284892372
261876219118.9648985290-356.964898529045
272175721129.8939205317627.106079468262
282050121865.0146098044-1364.01460980440
292318122042.39244886961138.60755113037
302301521998.52771505991016.47228494008
312282823028.0412693063-200.041269306311
322159722228.2994871935-631.299487193493
332300522704.8013737244300.198626275595
342224322115.2315957811127.768404218927
352072920952.1901617987-223.190161798678
361831019926.9979389178-1616.9979389178
371942719102.5729987587324.427001241292
381884919346.6526981843-497.652698184289
392181721890.9565687611-73.9565687610673
402110121983.9324573532-882.932457353157
412354622477.61831732411068.38168267594
422345623130.374288379325.625711620978
432364924418.3584332168-769.358433216772
442243223692.4535416175-1260.45354161749
452374523993.5246642741-248.5246642741
462387423530.9659176217343.034082378254
472232722565.3720483289-238.372048328859
482014321673.6195892778-1530.61958927781
492125220840.7340354881411.265964511864
502109421506.8154382875-412.815438287461
512180023173.1965867395-1373.19658673951
522248022358.7210107259121.278989274102
532305522776.9834281942278.016571805777
542335222554.0843791709797.91562082907
552317123132.448698425138.5513015749356
562069122526.9611669726-1835.96116697258
572318322399.4420172848783.557982715187
582241221606.0931157503805.906884249725
591895819709.8384717453-751.838471745263
601734718580.5557362545-1233.55573625446
611735317300.819064919352.1809350806783
621715317519.9476274078-366.947627407826
632014119132.2812530191008.71874698101
641969920083.3279558204-384.32795582037
652078020124.8236742848655.176325715155
662110120292.9050713577808.094928642293
672087121618.7056567799-747.705656779926
681957420239.8620421468-665.86204214681
692100220514.1432314818487.856768518228
702010520150.3115235848-45.311523584763
711777218789.8590567933-1017.85905679328
721611718126.1220907098-2009.12209070978


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.2319682377489750.4639364754979510.768031762251025
80.1137014250345410.2274028500690810.88629857496546
90.05144257317337880.1028851463467580.948557426826621
100.02399180396878010.04798360793756030.97600819603122
110.04672721154780250.0934544230956050.953272788452198
120.2273530139375510.4547060278751020.772646986062449
130.1578368054647550.315673610929510.842163194535245
140.1344380542025680.2688761084051360.865561945797432
150.1016622195920790.2033244391841580.898337780407921
160.0982443977326770.1964887954653540.901755602267323
170.08431850460424360.1686370092084870.915681495395756
180.07986759215882420.1597351843176480.920132407841176
190.07756245087412310.1551249017482460.922437549125877
200.05788235396795450.1157647079359090.942117646032046
210.04366025426906800.08732050853813590.956339745730932
220.05367390011882550.1073478002376510.946326099881175
230.05394281240386280.1078856248077260.946057187596137
240.1039109089023230.2078218178046460.896089091097677
250.09314278983888880.1862855796777780.906857210161111
260.1228066769099240.2456133538198480.877193323090076
270.1147556944024560.2295113888049120.885244305597544
280.3885791878153330.7771583756306660.611420812184667
290.3867353934599220.7734707869198450.613264606540078
300.3970137271862670.7940274543725340.602986272813733
310.3649175528786860.7298351057573710.635082447121314
320.3554429608741430.7108859217482860.644557039125857
330.3191798899943130.6383597799886260.680820110005687
340.2631631668717040.5263263337434090.736836833128296
350.2155391502840520.4310783005681040.784460849715948
360.3243044102170520.6486088204341040.675695589782948
370.3444885697268220.6889771394536440.655511430273178
380.3234199386745550.6468398773491110.676580061325445
390.2771452369895120.5542904739790250.722854763010488
400.3021580984531600.6043161969063190.69784190154684
410.362245289864080.724490579728160.63775471013592
420.3595401498988210.7190802997976410.640459850101179
430.3175212528220610.6350425056441210.68247874717794
440.3009162190170740.6018324380341470.699083780982926
450.2410437315425080.4820874630850170.758956268457492
460.2006920771352790.4013841542705580.799307922864721
470.1650660763428670.3301321526857350.834933923657132
480.1635555180017190.3271110360034380.836444481998281
490.2051167370722320.4102334741444640.794883262927768
500.1599461131853790.3198922263707590.84005388681462
510.1923632798437370.3847265596874750.807636720156263
520.1515706362957890.3031412725915780.848429363704211
530.1211574276984750.2423148553969490.878842572301525
540.1003146444917390.2006292889834790.89968535550826
550.09530347188000170.1906069437600030.904696528119998
560.3552654501837370.7105309003674750.644734549816263
570.2793841450718890.5587682901437770.720615854928111
580.2308486841339170.4616973682678330.769151315866083
590.1998557304233840.3997114608467680.800144269576616
600.2276073650706580.4552147301413160.772392634929342
610.2221008405271210.4442016810542420.777899159472879
620.1948808863829610.3897617727659220.805119113617039
630.3653329274451170.7306658548902340.634667072554883
640.3045956000828160.6091912001656320.695404399917184
650.2087681271490270.4175362542980540.791231872850973


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.0169491525423729OK
10% type I error level30.0508474576271186OK