Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 9330.58695652173 + 107.620600414074M1[t] -635.532091097308M2[t] -287.827639751553M3[t] + 8.74534161490695M4[t] -879.764492753623M5[t] + 75.725672877847M6[t] -309.617494824017M7[t] -141.293995859213M8[t] -196.97049689441M9[t] + 367.186335403727M10[t] + 234.50983436853M11[t] + 11.0098343685301t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)9330.58695652173136.43239768.389800
M1107.620600414074162.9848390.66030.51150.25575
M2-635.532091097308162.916845-3.9010.0002380.000119
M3-287.827639751553162.863941-1.76730.0821010.04105
M48.74534161490695169.4070110.05160.9589950.479497
M5-879.764492753623169.297972-5.19652e-061e-06
M675.725672877847169.2034140.44750.6560430.328022
M7-309.617494824017169.123363-1.83070.0719490.035975
M8-141.293995859213169.057838-0.83580.4064920.203246
M9-196.97049689441169.006856-1.16550.2482980.124149
M10367.186335403727168.9704322.17310.0336040.016802
M11234.50983436853168.9485731.38810.1700880.085044
t11.00983436853011.5691227.016600


Multiple Linear Regression - Regression Statistics
Multiple R0.846483642463992
R-squared0.716534556959107
Adjusted R-squared0.66167027766087
F-TEST (value)13.0601288511253
F-TEST (DF numerator)12
F-TEST (DF denominator)62
p-value8.07798272717264e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation292.614891203775
Sum Squared Residuals5308655.42236023


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
197009449.21739130438250.782608695625
290818717.07453416149363.925465838511
390849075.788819875788.21118012422472
497439383.37163561077359.628364389235
585878505.8716356107781.1283643892347
697319472.37163561077258.628364389235
795639098.03830227743464.961697722568
899989277.37163561077720.628364389235
994379232.7049689441204.295031055902
10100389807.87163561077230.128364389235
1199189686.2049689441231.795031055902
1292529462.7049689441-210.704968944098
1397379581.3354037267155.664596273298
1490358849.19254658385185.80745341615
1591339207.90683229814-74.9068322981358
1694879515.48964803313-28.4896480331257
1787008637.9896480331362.0103519668744
1896279604.4896480331322.5103519668742
1989479230.15631469979-283.156314699792
2092839409.48964803313-126.489648033126
2188299364.82298136646-535.822981366459
2299479939.989648033137.01035196687426
2396289818.32298136646-190.322981366459
2493189594.82298136646-276.822981366459
2596059713.45341614906-108.453416149063
2686408981.31055900621-341.310559006211
2792149340.0248447205-126.024844720497
2895679647.60766045549-80.6076604554863
2985478770.10766045549-223.107660455486
3091859736.60766045549-551.607660455487
3194709362.27432712215107.725672877847
3291239541.60766045549-418.607660455486
3392789496.94099378882-218.94099378882
341017010072.107660455597.8923395445137
3594349950.44099378882-516.44099378882
3696559726.94099378882-71.9409937888198
3794299845.57142857142-416.571428571424
3887399113.42857142857-374.428571428572
3995529472.1428571428679.8571428571429
4096879779.72567287785-92.725672877847
4190198902.22567287785116.774327122153
4296729868.72567287785-196.725672877847
4392069494.39233954451-288.392339544514
4490699673.72567287785-604.725672877847
4597889629.05900621118158.94099378882
461031210204.2256728778107.774327122153
471010510082.559006211222.4409937888196
4898639859.059006211183.94099378881956
4996569977.68944099378-321.689440993784
5092959245.5465838509349.4534161490679
5199469604.26086956522341.739130434782
5297019911.84368530021-210.843685300208
5390499034.3436853002114.6563146997923
541019010000.8436853002189.156314699792
5597069626.5103519668779.4896480331257
5697659805.84368530021-40.8436853002077
5798939761.17701863354131.822981366459
58999410336.3436853002-342.343685300208
591043310214.6770186335218.322981366459
60100739991.1770186335481.8229813664589
611011210109.80745341612.19254658385491
6292669377.66459627329-111.664596273293
6398209736.3788819875883.6211180124216
641009710043.961697722653.0383022774317
6591159166.46169772257-51.4616977225684
661041110132.9616977226278.038302277432
6796789758.62836438923-80.6283643892349
68104089937.96169772257470.038302277432
69101539893.2950310559259.704968944098
701036810468.4616977226-100.461697722568
711058110346.7950310559234.204968944098
721059710123.2950310559473.704968944098
731068010241.9254658385438.074534161494
7497389509.78260869565228.217391304347
7595569868.49689440994-312.496894409939


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
160.08579503247803060.1715900649560610.914204967521969
170.05249914236284970.1049982847256990.94750085763715
180.02310439656674660.04620879313349320.976895603433253
190.231495210219770.4629904204395410.76850478978023
200.4557925362952230.9115850725904450.544207463704777
210.5046248547684910.9907502904630190.495375145231509
220.4376776662035580.8753553324071160.562322333796442
230.3403518716684340.6807037433368670.659648128331566
240.3108558602279990.6217117204559980.689144139772001
250.2672363368810970.5344726737621940.732763663118903
260.206849883256790.4136997665135810.79315011674321
270.2399162526469080.4798325052938150.760083747353092
280.205631454710160.4112629094203210.79436854528984
290.1532689585733140.3065379171466280.846731041426686
300.1730084614320770.3460169228641530.826991538567924
310.2680029981810830.5360059963621670.731997001818917
320.2614164209755380.5228328419510750.738583579024462
330.268458916033420.5369178320668390.73154108396658
340.3429951291659310.6859902583318630.657004870834069
350.3587736747274710.7175473494549410.641226325272529
360.4319057185873550.863811437174710.568094281412645
370.3803629450068050.760725890013610.619637054993195
380.3291008768387070.6582017536774140.670899123161293
390.4505050033159060.9010100066318120.549494996684094
400.4031901999959860.8063803999919720.596809800004014
410.4850941277350230.9701882554700470.514905872264977
420.4543171020715930.9086342041431860.545682897928407
430.3807562718644430.7615125437288860.619243728135557
440.6061268541454770.7877462917090470.393873145854523
450.6749967690605830.6500064618788340.325003230939417
460.7522907682633550.4954184634732910.247709231736645
470.7288119200816720.5423761598366560.271188079918328
480.7041387281107150.591722543778570.295861271889285
490.7471268255805490.5057463488389030.252873174419451
500.6994219913515070.6011560172969870.300578008648493
510.9162245616856160.1675508766287690.0837754383143844
520.8726870594305430.2546258811389140.127312940569457
530.83758669320.3248266135999990.1624133068
540.7913207126358060.4173585747283880.208679287364194
550.7894838579562990.4210322840874010.210516142043701
560.7759253356027750.4481493287944510.224074664397225
570.6730586411975130.6538827176049740.326941358802487
580.5394523088143480.9210953823713030.460547691185652
590.4161104422446240.8322208844892490.583889557755376


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.0227272727272727OK
10% type I error level10.0227272727272727OK