Multiple Linear Regression - Estimated Regression Equation
ALGEMENEECONOMISCHSITUATIE[t] = + 177.987001468587 -0.0889106703726476JAARTAL[t] + 3.70130403074556CONSUMENTENVERTROUWEN[t] + 0.937369432584482`WERKLOOSHEIDINBELGIË`[t] -0.77658526223252`FINANCIËLESITUATIEVANDEGEZINNEN`[t] -0.827398659996597SPAARVERMOGENVANDEGEZINNEN[t] -0.0313111165458284t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)177.98700146858771.2759892.49720.0150220.007511
JAARTAL-0.08891067037264760.035557-2.50050.0148920.007446
CONSUMENTENVERTROUWEN3.701304030745560.1016136.426500
`WERKLOOSHEIDINBELGIË`0.9373694325844820.02549536.766700
`FINANCIËLESITUATIEVANDEGEZINNEN`-0.776585262232520.14078-5.51631e-060
SPAARVERMOGENVANDEGEZINNEN-0.8273986599965970.053355-15.507400
t-0.03131111654582840.010857-2.88410.0052960.002648


Multiple Linear Regression - Regression Statistics
Multiple R0.99385482096443
R-squared0.98774740515424
Adjusted R-squared0.986633532895535
F-TEST (value)886.769014520752
F-TEST (DF numerator)6
F-TEST (DF denominator)66
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.13371599143121
Sum Squared Residuals84.8305886489718


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1-20-18.8676327061752-1.13236729382476
2-8-8.311712575579320.311712575579323
3-15-15.32871210469630.328712104696304
4-13-13.51659177456440.516591774564366
5-6-5.27222901877265-0.727770981227345
60-2.027848946826562.02784894682656
755.36978749667737-0.369787496677374
8-1-0.439087656915212-0.560912343084788
9-5-3.64481238269868-1.35518761730132
1042.958465269223971.04153473077603
11-3-3.07563082588780.075630825887803
1232.598659565368180.40134043463182
1389.26524474806026-1.26524474806026
1435.76264757292845-2.76264757292845
1533.21255366155817-0.212553661558169
1676.731838832389740.268161167610262
1742.515963925794841.48403607420516
18-4-2.31151825156652-1.68848174843348
19-6-6.640003628921010.640003628921012
2087.3218585408460.678141459154003
2120.4934036541529471.50659634584705
22-1-0.899379279457069-0.100620720542931
23-2-2.513614216016780.513614216016781
2401.00419869189895-1.00419869189895
25109.2910308683950.708969131605007
2631.160743905164581.83925609483542
2766.2949966734567-0.294996673456696
2877.00217354653482-0.00217354653481666
29-4-3.01496519749379-0.985034802506214
30-5-6.244167731514041.24416773151405
31-7-4.99133081661061-2.00866918338939
32-10-12.0701274187232.07012741872304
33-21-20.5727961204215-0.427203879578548
34-22-21.1988482266326-0.801151773367401
35-16-14.4594822957136-1.54051770428642
36-25-25.84436215036260.844362150362595
37-22-23.13621256795281.13621256795279
38-22-21.4534358402525-0.546564159747534
39-19-19.55793230403830.557932304038316
40-21-19.7358010080067-1.26419899199331
41-31-30.2823367222858-0.717663277714241
42-28-28.11833672392730.11833672392734
43-23-23.7223499531090.722349953109015
44-17-16.9898175414758-0.0101824585241963
45-12-12.28597464607770.28597464607771
46-14-12.8612133545248-1.13878664547522
47-18-17.8961429440565-0.103857055943453
48-16-15.3680233242633-0.631976675736709
49-22-23.28520226160381.28520226160375
50-9-9.257349197727120.257349197727115
51-10-10.10598254728570.105982547285742
52-10-8.51224963938722-1.48775036061278
530-1.020905494870241.02090549487024
5431.127960672311121.87203932768888
5522.27766033391248-0.27766033391248
5644.08978066404437-0.0897806640443704
57-3-4.650603112178571.65060311217857
5800.090429807580466-0.090429807580466
59-1-0.212543500152847-0.787456499847153
60-7-6.44029293128431-0.559707068715689
6123.19867099424755-1.19867099424755
6231.705390505507171.29460949449283
63-3-4.438676362192491.43867636219249
64-5-6.222039446163891.22203944616389
650-0.3881323198118150.388132319811815
66-3-2.27312219931137-0.72687780068863
67-7-8.586317214422711.58631721442271
68-7-8.151405742058351.15140574205835
69-7-5.5213163042189-1.4786836957811
70-4-2.7031959492212-1.2968040507788
71-3-2.4317083453805-0.568291654619497
72-6-5.33360006495074-0.666399935049264
73-10-8.28638704231161-1.71361295768839


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.8648400449844290.2703199100311430.135159955015571
110.7659427913974920.4681144172050160.234057208602508
120.6450697384325820.7098605231348370.354930261567418
130.6542766297498190.6914467405003620.345723370250181
140.797931343321750.40413731335650.20206865667825
150.8296203992712780.3407592014574450.170379600728722
160.8163855792871860.3672288414256280.183614420712814
170.8182324548783350.3635350902433310.181767545121665
180.8705838232438360.2588323535123290.129416176756164
190.8289186531755750.3421626936488510.171081346824425
200.7695686650603290.4608626698793430.230431334939672
210.7338640720935270.5322718558129450.266135927906473
220.7120591885789680.5758816228420650.287940811421032
230.6380355785173730.7239288429652530.361964421482627
240.6094075585368460.7811848829263080.390592441463154
250.5614305250007380.8771389499985230.438569474999262
260.6649748712396650.670050257520670.335025128760335
270.5959749491435230.8080501017129540.404025050856477
280.5197813193074460.9604373613851090.480218680692554
290.5125944505580560.9748110988838870.487405549441944
300.4791467216149990.9582934432299980.520853278385001
310.7227080679187920.5545838641624160.277291932081208
320.8613100226344340.2773799547311310.138689977365566
330.8184358661219290.3631282677561430.181564133878071
340.779333937903570.4413321241928590.220666062096429
350.7869256963269960.4261486073460080.213074303673004
360.8076076039482210.3847847921035580.192392396051779
370.8762265899127660.2475468201744680.123773410087234
380.8343705663411750.3312588673176490.165629433658825
390.8056811016036310.3886377967927380.194318898396369
400.7887081005699120.4225837988601750.211291899430088
410.7461306365685760.5077387268628470.253869363431423
420.7130946908653440.5738106182693130.286905309134656
430.6688237486028310.6623525027943380.331176251397169
440.6026913784386450.7946172431227110.397308621561355
450.5301610250518470.9396779498963060.469838974948153
460.5074225230209590.9851549539580830.492577476979041
470.454336602827760.908673205655520.54566339717224
480.479293343940040.958586687880080.52070665605996
490.4495229730505990.8990459461011990.5504770269494
500.3965850568704610.7931701137409220.60341494312954
510.3274895883796780.6549791767593550.672510411620322
520.9739207480677070.05215850386458560.0260792519322928
530.9634965294892660.07300694102146860.0365034705107343
540.9673345900205960.06533081995880880.0326654099794044
550.967097026320950.0658059473580980.032902973679049
560.9453188522842670.1093622954314660.0546811477157332
570.9183569328378440.1632861343243120.0816430671621562
580.921523556953920.1569528860921590.0784764430460793
590.8701411370893950.2597177258212090.129858862910605
600.8103090218388210.3793819563223570.189690978161179
610.764205869258780.4715882614824390.235794130741219
620.7225275489541890.5549449020916230.277472451045811
630.6713002272859060.6573995454281870.328699772714094


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 level40.0740740740740741OK