Multiple Linear Regression - Estimated Regression Equation

slaagkans[t] = + 21.2435270406808 -0.189021294324606verzekeraar[t] + 0.546658570171708kost[t] + 0.788682667921521grootte[t] + 0.0270026552096039snelheid[t] + 0.345099845668745maand[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	21.2435270406808	24.710473	0.8597	0.394616	0.197308
verzekeraar	-0.189021294324606	2.766775	-0.0683	0.945842	0.472921
kost	0.546658570171708	0.158908	3.4401	0.001284	0.000642
grootte	0.788682667921521	4.447924	0.1773	0.860075	0.430037
snelheid	0.0270026552096039	0.134153	0.2013	0.841405	0.420703
maand	0.345099845668745	1.134591	0.3042	0.762438	0.381219

Multiple Linear Regression - Regression Statistics
Multiple R	0.479791384134689
R-squared	0.230199772289880
Adjusted R-squared	0.142722473686458
F-TEST (value)	2.63153727841424
F-TEST (DF numerator)	5
F-TEST (DF denominator)	44
p-value	0.0363218943091439
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	27.7904116050644
Sum Squared Residuals	33981.5069958716

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	73	66.5913029636444	6.4086970363556
2	28	29.2278267061414	-1.22782670614140
3	40	33.7884662270152	6.21153377298481
4	79	74.5417180149841	4.45828198501587
5	75	68.3717814827618	6.62821851723822
6	21	45.9059702515849	-24.9059702515849
7	16	40.8742385495194	-24.8742385495194
8	81	58.3535199386703	22.6464800613297
9	90	51.3642663482893	38.6357336517107
10	87	63.0922795222357	23.9077204777643
11	99	58.9952534044508	40.0047465955492
12	54	56.701342662365	-2.70134266236496
13	53	73.5065341939744	-20.5065341939744
14	6	62.5598800408435	-56.5598800408435
15	71	59.412814131667	11.5871858683329
16	93	69.1916027460129	23.8083972539871
17	82	69.0350043629585	12.9649956370415
18	32	69.9396706422864	-37.9396706422864
19	93	77.8506888327145	15.1493111672855
20	24	63.2509722106068	-39.2509722106068
21	96	66.4594955815581	29.5405044184419
22	88	78.8496034278642	9.15039657213578
23	83	29.9625188985102	53.0374811014898
24	23	46.3563009611064	-23.3563009611064
25	23	46.0783539040421	-23.0783539040421
26	20	54.0028717520872	-34.0028717520872
27	33	46.660622172898	-13.660622172898
28	88	65.5140402583913	22.4859597416087
29	42	34.9631058042881	7.03689419571192
30	98	64.9504109821951	33.0495890178049
31	34	41.4150705063765	-7.41507050637646
32	59	61.2495521527782	-2.24955215277821
33	26	30.3148653378247	-4.31486533782468
34	64	63.379780935049	0.620219064951007
35	13	63.0883295169072	-50.0883295169072
36	6	41.663616383533	-35.663616383533
37	49	36.8361261330018	12.1638738669982
38	3	37.9052012768741	-34.9052012768741
39	87	49.9219358094036	37.0780641905964
40	77	58.117966085154	18.882033914846
41	70	76.7212993646978	-6.72129936469776
42	76	30.3628322234458	45.6371677765542
43	82	68.4207804798163	13.5792195201837
44	12	53.8866455735835	-41.8866455735835
45	44	40.1473816640818	3.85261833591824
46	63	40.599645091627	22.4003549083730
47	35	44.3464233300635	-9.3464233300635
48	69	51.7164360314108	17.2835639685892
49	10	30.9765395379208	-20.9765395379208
50	36	58.5771155907836	-22.5771155907836

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
9	0.537032818778377	0.925934362443246	0.462967181221623
10	0.487884027537456	0.975768055074912	0.512115972462544
11	0.411889610180891	0.823779220361783	0.588110389819109
12	0.32829621448542	0.65659242897084	0.67170378551458
13	0.293772201437280	0.587544402874559	0.70622779856272
14	0.73244412037935	0.5351117592413	0.26755587962065
15	0.653719444377639	0.692561111244723	0.346280555622361
16	0.614620997907952	0.770758004184097	0.385379002092048
17	0.521757142936793	0.956485714126414	0.478242857063207
18	0.583784142951404	0.832431714097191	0.416215857048596
19	0.50429737582904	0.99140524834192	0.49570262417096
20	0.58622321588836	0.827553568223279	0.413776784111640
21	0.580486125822995	0.839027748354011	0.419513874177006
22	0.497453739674429	0.994907479348857	0.502546260325571
23	0.669542517240056	0.660914965519888	0.330457482759944
24	0.638018530533255	0.72396293893349	0.361981469466745
25	0.601550256169436	0.796899487661128	0.398449743830564
26	0.643174623320532	0.713650753358935	0.356825376679468
27	0.57580084971642	0.84839830056716	0.42419915028358
28	0.54026254580832	0.91947490838336	0.45973745419168
29	0.470684012688482	0.941368025376964	0.529315987311518
30	0.548578505079109	0.902842989841782	0.451421494920891
31	0.459533155585378	0.919066311170756	0.540466844414622
32	0.368513731662366	0.737027463324732	0.631486268337634
33	0.285493211950997	0.570986423901994	0.714506788049003
34	0.204934796032072	0.409869592064144	0.795065203967928
35	0.317779778895449	0.635559557790898	0.682220221104551
36	0.340149363958446	0.680298727916893	0.659850636041554
37	0.258475040950477	0.516950081900954	0.741524959049523
38	0.330395065139085	0.66079013027817	0.669604934860915
39	0.27007958131117	0.54015916262234	0.72992041868883
40	0.367744887303538	0.735489774607077	0.632255112696462
41	0.262976227988480	0.525952455976959	0.73702377201152

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	0	0	OK
10% type I error level	0	0	OK