Multiple Linear Regression - Estimated Regression Equation
Huurprijs[t] = + 261.559850248446 + 27.9706524613068Slaapkamers[t] + 2.24357262516708Bewoonbareopp[t] + 69.8338996357666Terras[t] + 1.16761510821164Garage[t] + 95.1289869483621Nieuwbouw[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)261.55985024844651.8397475.04559e-064e-06
Slaapkamers27.970652461306825.3499651.10340.2759990.137999
Bewoonbareopp2.243572625167080.5128314.37497.6e-053.8e-05
Terras69.833899635766629.7233552.34950.0234630.011731
Garage1.1676151082116414.4776350.08060.9360950.468047
Nieuwbouw95.128986948362124.4937853.88380.000350.000175


Multiple Linear Regression - Regression Statistics
Multiple R0.790226051322629
R-squared0.624457212188954
Adjusted R-squared0.580789446164414
F-TEST (value)14.3001868205949
F-TEST (DF numerator)5
F-TEST (DF denominator)43
p-value3.0025185782101e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation83.6759928581479
Sum Squared Residuals301071.886574263


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1475452.11551268108522.8844873189153
2530509.68376823171420.3162317682862
3550592.667778805242-42.6677788052421
4550628.401626701238-78.401626701238
5625664.433926252935-39.433926252935
6650677.74651773598-27.7465177359805
7650605.57738788379144.4226121162094
8720838.087955082145-118.087955082145
9795751.84160104319543.1583989568052
10515580.373958162451-65.3739581624513
11535614.027547539957-79.0275475399574
12550505.96125568509444.0387443149056
13600598.2308815725321.76911842746825
14600652.961091429166-52.9610914291661
15660653.21606312716.78393687290036
16695625.15375307453769.8462469254633
17720711.4572937901878.54270620981256
18750681.3347262949768.6652737050302
19750787.830420637124-37.8304206371243
20850769.7329953678380.2670046321694
21850749.449184150071100.550815849929
22875795.4600752039779.5399247960297
23900783.194431118833116.805568881167
24595683.30962050327-88.30962050327
25765842.575100332479-77.575100332479
26495586.864174178739-91.8641741787393
27525514.78670191780610.2132980821943
28525510.29955666747214.7004433325284
29595591.5918212882873.40817871171328
30650633.97919930724816.0208006927520
31695743.483098978284-48.4830989782842
32615600.28296353336814.7170364666322
33460566.820864820193-106.820864820193
34650707.988919380108-57.9889193801079
35650652.975561267886-2.97556126788644
36475506.364238089591-31.3642380895913
37530556.770616802569-26.7706168025689
38575697.938671362484-122.938671362484
39650674.335330002602-24.3353300026018
40650692.312087561592-42.312087561592
41875785.34634615274489.653653847256
42500626.937156618506-126.937156618506
43625524.284642533274100.715357466726
44730736.079405990325-6.07940599032447
45750820.167550638462-70.1675506384617
46700544.193647904191155.806352095809
47830762.91061990107367.0893800989268
48995709.15653448832285.843465511680
49850849.305818207980.694181792019827


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.1314320748797180.2628641497594360.868567925120282
100.05217408573759430.1043481714751890.947825914262406
110.02088001436191880.04176002872383750.979119985638081
120.007336802724216710.01467360544843340.992663197275783
130.002836410954287560.005672821908575120.997163589045712
140.001148051378332080.002296102756664160.998851948621668
150.001556975406814900.003113950813629810.998443024593185
160.001470403046687460.002940806093374920.998529596953313
170.0006398138968205440.001279627793641090.99936018610318
180.01035917888631540.02071835777263090.989640821113685
190.005333491046475730.01066698209295150.994666508953524
200.01508258453466700.03016516906933390.984917415465333
210.01276195462479780.02552390924959550.987238045375202
220.01532458029427930.03064916058855860.98467541970572
230.02185088993727300.04370177987454610.978149110062727
240.04445814552448690.08891629104897380.955541854475513
250.04574351397721280.09148702795442570.954256486022787
260.06758473341257280.1351694668251460.932415266587427
270.04213032342203690.08426064684407380.957869676577963
280.02614643755755380.05229287511510750.973853562442446
290.01661821638481200.03323643276962410.983381783615188
300.009704129884690230.01940825976938050.99029587011531
310.006492127365141920.01298425473028380.993507872634858
320.003788679153559510.007577358307119030.99621132084644
330.005612758910551440.01122551782110290.994387241089449
340.003532525019149170.007065050038298330.99646747498085
350.001648035583139750.003296071166279490.99835196441686
360.000959940767679190.001919881535358380.99904005923232
370.0009238911923770770.001847782384754150.999076108807623
380.002192162254243000.004384324508486010.997807837745757
390.001038042874666560.002076085749333120.998961957125333
400.0006468476482675370.001293695296535070.999353152351732


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level130.40625NOK
5% type I error level250.78125NOK
10% type I error level290.90625NOK