Multiple Linear Regression - Estimated Regression Equation

vrijetijdsbesteding[t] = + 110.49 -1.72600000000005M1[t] -1.34400000000001M2[t] -1.28000000000001M3[t] -0.76400000000001M4[t] -0.722000000000008M5[t] -0.384000000000008M6[t] -0.216000000000008M7[t] + 0.165999999999991M8[t] + 1.49600000000000M9[t] + 1.69999999999999M10[t] -0.187500000000006M11[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)	110.49	3.049833	36.2282	0	0
M1	-1.72600000000005	4.09178	-0.4218	0.67512	0.33756
M2	-1.34400000000001	4.09178	-0.3285	0.744052	0.372026
M3	-1.28000000000001	4.09178	-0.3128	0.75583	0.377915
M4	-0.76400000000001	4.09178	-0.1867	0.852705	0.426352
M5	-0.722000000000008	4.09178	-0.1765	0.860714	0.430357
M6	-0.384000000000008	4.09178	-0.0938	0.925639	0.462819
M7	-0.216000000000008	4.09178	-0.0528	0.958129	0.479064
M8	0.165999999999991	4.09178	0.0406	0.967815	0.483907
M9	1.49600000000000	4.09178	0.3656	0.716331	0.358166
M10	1.69999999999999	4.09178	0.4155	0.679732	0.339866
M11	-0.187500000000006	4.313115	-0.0435	0.965513	0.482757

Multiple Linear Regression - Regression Statistics
Multiple R	0.184116543409472
R-squared	0.0338989015570519
Adjusted R-squared	-0.197125274157566
F-TEST (value)	0.146733134972536
F-TEST (DF numerator)	11
F-TEST (DF denominator)	46
p-value	0.999225903166059
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	6.09966569825223
Sum Squared Residuals	1711.47239500000

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	101.76	108.764000000000	-7.00400000000016
2	102.37	109.146	-6.77599999999999
3	102.38	109.21	-6.83000000000001
4	102.86	109.726	-6.866
5	102.87	109.768	-6.898
6	102.92	110.106	-7.186
7	102.95	110.274	-7.324
8	103.02	110.656	-7.636
9	104.08	111.986	-7.906
10	104.16	112.19	-8.03
11	104.24	110.3025	-6.06250000000001
12	104.33	110.49	-6.16000000000001
13	104.73	108.764	-4.03399999999995
14	104.86	109.146	-4.286
15	105.03	109.21	-4.18
16	105.62	109.726	-4.10599999999999
17	105.63	109.768	-4.13800000000001
18	105.63	110.106	-4.476
19	105.94	110.274	-4.334
20	106.61	110.656	-4.046
21	107.69	111.986	-4.29600000000000
22	107.78	112.19	-4.41
23	107.93	110.3025	-2.37250000000000
24	108.48	110.49	-2.01000000000000
25	108.14	108.764	-0.623999999999958
26	108.48	109.146	-0.665999999999992
27	108.48	109.21	-0.729999999999993
28	108.89	109.726	-0.835999999999997
29	108.93	109.768	-0.837999999999994
30	109.21	110.106	-0.896000000000004
31	109.47	110.274	-0.804000000000003
32	109.8	110.656	-0.856000000000001
33	111.73	111.986	-0.255999999999998
34	111.85	112.19	-0.340000000000002
35	112.12	110.3025	1.81750000000000
36	112.15	110.49	1.66000000000000
37	112.17	108.764	3.40600000000004
38	112.67	109.146	3.52400000000000
39	112.8	109.21	3.59
40	113.44	109.726	3.714
41	113.53	109.768	3.762
42	114.53	110.106	4.42400000000000
43	114.51	110.274	4.236
44	115.05	110.656	4.394
45	116.67	111.986	4.684
46	117.07	112.19	4.88
47	116.92	110.3025	6.6175
48	117	110.49	6.50999999999999
49	117.02	108.764	8.25600000000004
50	117.35	109.146	8.204
51	117.36	109.21	8.15
52	117.82	109.726	8.094
53	117.88	109.768	8.112
54	118.24	110.106	8.134
55	118.5	110.274	8.226
56	118.8	110.656	8.144
57	119.76	111.986	7.774
58	120.09	112.19	7.9

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
15	0.0645893929315995	0.129178785863199	0.9354106070684
16	0.0359893264042393	0.0719786528084787	0.96401067359576
17	0.0213879206131229	0.0427758412262459	0.978612079386877
18	0.0136170394310909	0.0272340788621817	0.98638296056891
19	0.0101066555341159	0.0202133110682319	0.989893344465884
20	0.00963159584388155	0.0192631916877631	0.990368404156118
21	0.00996493520835916	0.0199298704167183	0.99003506479164
22	0.0112566868735290	0.0225133737470579	0.98874331312647
23	0.0110864841604224	0.0221729683208449	0.988913515839578
24	0.0121488516846593	0.0242977033693186	0.98785114831534
25	0.0209377049293228	0.0418754098586457	0.979062295070677
26	0.0325552412018408	0.0651104824036817	0.96744475879816
27	0.0471685673852682	0.0943371347705364	0.952831432614732
28	0.0659306624002647	0.131861324800529	0.934069337599735
29	0.0923365843578951	0.184673168715790	0.907663415642105
30	0.140624188991067	0.281248377982135	0.859375811008933
31	0.210200834755615	0.42040166951123	0.789799165244385
32	0.312124005241855	0.62424801048371	0.687875994758145
33	0.444300268001602	0.888600536003204	0.555699731998398
34	0.613391200454309	0.773217599091382	0.386608799545691
35	0.66289280374485	0.674214392510299	0.337107196255150
36	0.701594229772474	0.596811540455053	0.298405770227526
37	0.766452204323642	0.467095591352717	0.233547795676358
38	0.810691125505356	0.378617748989288	0.189308874494644
39	0.839769048191784	0.320461903616432	0.160230951808216
40	0.856206312719432	0.287587374561137	0.143793687280568
41	0.86615000140447	0.267699997191059	0.133849998595530
42	0.853261402125933	0.293477195748133	0.146738597874067
43	0.838073030879997	0.323853938240006	0.161926969120003

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	9	0.310344827586207	NOK
10% type I error level	12	0.413793103448276	NOK