Multiple Linear Regression - Estimated Regression Equation
CM+D[t] = + 44.9403520933643 + 0.355766125652141`PE+PC`[t] -0.231653308417249happiness[t] + 0.263610054527117depression[t] -0.466508840964572connected[t] -0.147481738970619separated[t] + 0.0813939733229003populariteit[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)44.940352093364350.0872010.89720.3714010.185701
`PE+PC`0.3557661256521410.111663.18620.0018410.000921
happiness-0.2316533084172491.290405-0.17950.8578350.428917
depression0.2636100545271170.5873240.44880.6543690.327184
connected-0.4665088409645720.666857-0.69960.4855650.242783
separated-0.1474817389706191.023207-0.14410.8856360.442818
populariteit0.08139397332290030.5900470.13790.8905170.445259


Multiple Linear Regression - Regression Statistics
Multiple R0.293830789401748
R-squared0.0863365328004547
Adjusted R-squared0.0402694672273682
F-TEST (value)1.87414873785438
F-TEST (DF numerator)6
F-TEST (DF denominator)119
p-value0.0907825194364746
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation6.9205070293393
Sum Squared Residuals5699.31668763302


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
13832.89824440319125.10175559680876
23630.05211539797415.94788460202587
32333.6097766544955-10.6097766544955
43031.1194137749306-1.11941377493055
52632.186712151887-6.18671215188697
62631.4751799005827-5.47517990058269
73028.66368422126761.33631577873236
82732.5424782775391-5.54247827753911
93431.63796784722852.36203215277151
102831.8126835277465-3.81268352774652
113633.96554278014772.03445721985232
124233.96554278014778.03445721985232
133132.3495000985328-1.34950009853277
142631.4751799005827-5.47517990058269
151630.0867487238762-14.0867487238762
162331.6379678472285-8.6379678472285
174534.67707503145210.322924968548
183034.5654908257685-4.56549082576852
194531.119413774930513.8805862250695
203031.7193618205514-1.71936182055139
212433.2540105288434-9.2540105288434
222930.7982809751805-1.79828097518049
233032.5242157790508-2.5242157790508
243133.7725646011413-2.77256460114134
253430.21490334461993.78509665538007
264136.81167178536484.18832821463519
273732.89824440319134.10175559680874
283331.47517990058271.52482009941731
294830.214903344619917.7850966553801
304430.296297317942813.7037026820572
312930.9264355959242-1.92643559592421
324435.37034478426798.62965521573207
334334.83986297809788.16013702190224
343133.0610323498371-2.06103234983706
352832.8982444031913-4.89824440319126
362632.3495000985328-6.34950009853277
373031.1194137749305-1.11941377493055
382731.3974127793962-4.39741277939621
393433.25401052884340.745989471156603
404730.052115397974116.9478846020259
413734.49109145616242.50890854383757
422731.8309460262348-4.83094602623483
433031.8309460262348-1.83094602623483
443640.532120988532-4.53212098853202
453931.83094602623487.16905397376517
463231.83094602623480.169053973765168
472531.8309460262348-6.83094602623483
481928.6290508953656-9.62905089536556
492932.186712151887-3.18671215188697
502632.1684496533987-6.16844965339866
513130.08674872387620.913251276123796
523132.186712151887-1.18671215188697
533131.0078295692471-0.00782956924710881
543931.47517990058277.5248200994173
552832.186712151887-4.18671215188697
562230.4078815236263-8.40788152362627
573131.4751799005827-0.475179900582691
583631.63796784722854.36203215277151
592830.4078815236263-2.40788152362627
603933.25401052884345.7459894711566
613532.1867121518872.81328784811303
623331.83094602623481.16905397376517
632731.4751799005827-4.47517990058269
643332.89824440319130.101755596808744
653131.1194137749305-0.119413774930549
663931.63796784722857.36203215277151
673733.06103234983713.93896765016294
682431.7193618205514-7.71936182055139
692832.5771116034412-4.57711160344119
703727.95215196996349.04784803003665
713233.0610323498371-1.06103234983706
723129.01945034691981.98054965308022
732929.3752164725719-0.37521647257192
744035.38860728275624.61139271724376
754032.70526622418497.29473377581509
761529.696349272322-14.696349272322
772729.6780867738337-2.67808677383367
783232.1684496533987-0.168449653398659
792832.186712151887-4.18671215188697
804136.61869360635854.38130639364153
814732.898244403191314.1017555968087
824235.38860728275626.61139271724376
833233.3651738076091-1.36517380760909
843333.8539585744642-0.85395857446424
852935.0328411571041-6.0328411571041
863732.34950009853284.65049990146723
873930.6520634435958.34793655640503
882930.7636476492784-1.76364764927841
893332.89824440319130.101755596808744
903131.1011512764422-0.101151276442236
912131.7193618205514-10.7193618205514
923634.83986297809781.16013702190224
933235.1956291037499-3.1956291037499
941531.4751799005827-16.4751799005827
952533.5915141560072-8.59151415600723
962830.0521153979741-2.05211539797413
973933.25401052884345.7459894711566
983128.96655452252942.03344547747061
994028.629050895365611.3709491046344
1002531.4751799005827-6.4751799005827
1013633.77256460114132.22743539885866
1022329.1476049676635-6.1476049676635
1033930.05211539797418.94788460202588
1043133.7725646011413-2.77256460114134
1052329.696349272322-6.69634927232199
1063131.6379678472285-0.637967847228491
1072832.8799819047029-4.87998190470294
1084731.456917402094415.5430825979056
1092532.0751279462035-7.07512794620353
1102630.389619025138-4.38961902513795
1112432.4170369123601-8.41703691236012
1123032.7866601975078-2.78666019750782
1132533.423793079206-8.423793079206
1144431.839766616686812.1602333833132
1153840.6135149618549-2.61351496185492
1163628.98481702101777.0151829789823
1173433.28864385474550.711356145254524
1184532.000728576597412.9992714234026
1192931.2822017215763-2.28220172157635
1202532.186712151887-7.18671215188697
1213033.2540105288434-3.2540105288434
1222732.1565219195264-5.15652191952643
1234433.416798475489210.5832015245108
1243136.4559056597127-5.45590565971267
1253533.60977665449551.39022334550446
1264737.16743791101699.83256208898305


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.6308657495517370.7382685008965260.369134250448263
110.6490103790980780.7019792418038430.350989620901922
120.7503222332523250.499355533495350.249677766747675
130.6530130554259380.6939738891481240.346986944574062
140.5817520197585910.8364959604828180.418247980241409
150.703769179994550.5924616400108990.29623082000545
160.7095464510056590.5809070979886820.290453548994341
170.7838431726686880.4323136546626240.216156827331312
180.7210713458353280.5578573083293440.278928654164672
190.8642948000052450.271410399989510.135705199994755
200.81849805555640.36300388888720.1815019444436
210.8467944516394750.3064110967210510.153205548360525
220.8117304842029150.376539031594170.188269515797085
230.7585339540761680.4829320918476650.241466045923832
240.6985400502095920.6029198995808170.301459949790409
250.6594862995631340.6810274008737320.340513700436866
260.6239804974080820.7520390051838350.376019502591918
270.573496954560310.8530060908793810.42650304543969
280.5053867326362660.9892265347274680.494613267363734
290.8032706149676560.3934587700646890.196729385032344
300.8711643575719340.2576712848561310.128835642428066
310.8458393921320.3083212157359990.154160607867999
320.8824521935983220.2350956128033550.117547806401678
330.8853833053387140.2292333893225720.114616694661286
340.8594507313439070.2810985373121850.140549268656093
350.8418379969339990.3163240061320020.158162003066001
360.8408928898105580.3182142203788840.159107110189442
370.803675661779420.392648676441160.19632433822058
380.7773284795885770.4453430408228460.222671520411423
390.7312295644664560.5375408710670880.268770435533544
400.8835364393787660.2329271212424680.116463560621234
410.8528327055879270.2943345888241460.147167294412073
420.8395233697996560.3209532604006870.160476630200344
430.8070803199295750.3858393601408490.192919680070425
440.775302335430190.4493953291396190.22469766456981
450.7704212293650450.4591575412699090.229578770634955
460.7266506608366090.5466986783267820.273349339163391
470.7306270745037130.5387458509925740.269372925496287
480.7855897698371110.4288204603257780.214410230162889
490.7522916802140570.4954166395718860.247708319785943
500.7440082191497930.5119835617004150.255991780850207
510.7124941315478760.5750117369042470.287505868452124
520.6655700718716980.6688598562566050.334429928128302
530.6167534609787620.7664930780424770.383246539021238
540.6217440070325230.7565119859349540.378255992967477
550.588365293372140.8232694132557210.411634706627861
560.6133168982914630.7733662034170740.386683101708537
570.5609148056239740.8781703887520520.439085194376026
580.5262347619114790.9475304761770430.473765238088521
590.4792017331927560.9584034663855120.520798266807244
600.4620632044363750.924126408872750.537936795563625
610.4174592800973730.8349185601947470.582540719902627
620.3671868944868980.7343737889737960.632813105513102
630.3374776365030590.6749552730061170.662522363496941
640.289814591804580.579629183609160.71018540819542
650.2455795402715850.4911590805431690.754420459728415
660.2477961023594730.4955922047189450.752203897640527
670.2193473876329470.4386947752658950.780652612367053
680.2316030419275020.4632060838550050.768396958072498
690.2188045085616550.437609017123310.781195491438345
700.2430492645483270.4860985290966550.756950735451673
710.2037500445559630.4075000891119250.796249955444037
720.1704817504670420.3409635009340840.829518249532958
730.1428623811210440.2857247622420890.857137618878956
740.1269485696369840.2538971392739670.873051430363016
750.1297640436730370.2595280873460740.870235956326963
760.2478257250792960.4956514501585920.752174274920704
770.212591211439320.4251824228786410.78740878856068
780.1756167488027750.351233497605550.824383251197225
790.1539473042670630.3078946085341260.846052695732937
800.1363306649850080.2726613299700160.863669335014992
810.2445628340405820.4891256680811650.755437165959418
820.2448792999184580.4897585998369160.755120700081542
830.2144377776374760.4288755552749510.785562222362524
840.1771960169699670.3543920339399340.822803983030033
850.1621336950540870.3242673901081740.837866304945913
860.1461035036596810.2922070073193610.85389649634032
870.1723394878347370.3446789756694740.827660512165263
880.138943416173790.2778868323475810.86105658382621
890.1088309240152250.217661848030450.891169075984775
900.08436459590149320.1687291918029860.915635404098507
910.1036716124035620.2073432248071250.896328387596438
920.0817381517826180.1634763035652360.918261848217382
930.06311772824649420.1262354564929880.936882271753506
940.1876612713202660.3753225426405320.812338728679734
950.2321315462514560.4642630925029120.767868453748544
960.1924830994204330.3849661988408660.807516900579567
970.1712310804162480.3424621608324960.828768919583752
980.1377924518505650.275584903701130.862207548149435
990.1924970681471150.3849941362942290.807502931852885
1000.1815470268518710.3630940537037410.818452973148129
1010.1479362422113870.2958724844227740.852063757788613
1020.1271348869988470.2542697739976930.872865113001153
1030.1464829046596860.2929658093193720.853517095340314
1040.1093208688074630.2186417376149250.890679131192537
1050.09954279075767560.1990855815153510.900457209242324
1060.06961442876452450.1392288575290490.930385571235475
1070.08990898056462030.1798179611292410.91009101943538
1080.132614750083140.265229500166280.86738524991686
1090.1104431039935950.2208862079871910.889556896006405
1100.1798260188463320.3596520376926640.820173981153668
1110.1262584243433330.2525168486866660.873741575656667
1120.08313919524680050.1662783904936010.9168608047532
1130.2338521600700040.4677043201400070.766147839929996
1140.1695873555895430.3391747111790860.830412644410457
1150.102914559498420.205829118996840.89708544050158
1160.1434090256635220.2868180513270440.856590974336478


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 level00OK