Multiple Linear Regression - Estimated Regression Equation
Months[t] = + 97.326923076923 -15.4317765567765M1[t] -25.2454212454212M2[t] -31.0590659340659M3[t] -21.8727106227106M4[t] -25.400641025641M5[t] -20.7857142857143M6[t] -5.24130036630036M7[t] -20.7930402930403M8[t] -14.5114468864469M9[t] -29.8965201465201M10[t] -29.6149267399267M11[t] -0.61492673992674t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)97.32692307692313.4785967.220900
M1-15.431776556776516.320848-0.94550.3478920.173946
M2-25.245421245421216.314823-1.54740.1266240.063312
M3-31.059065934065916.310136-1.90430.0613010.030651
M4-21.872710622710616.306787-1.34130.1844830.092241
M5-25.40064102564116.304777-1.55790.1241210.062061
M6-20.785714285714316.304107-1.27490.2068920.103446
M7-5.2413003663003616.935704-0.30950.7579450.378972
M8-20.793040293040316.929898-1.22820.2238060.111903
M9-14.511446886446916.925381-0.85740.3943860.197193
M10-29.896520146520116.922154-1.76670.0819720.040986
M11-29.614926739926716.920217-1.75030.0847910.042395
t-0.614926739926740.147804-4.16049.5e-054.8e-05


Multiple Linear Regression - Regression Statistics
Multiple R0.527695037155309
R-squared0.278462052238343
Adjusted R-squared0.145255046497730
F-TEST (value)2.09044599936866
F-TEST (DF numerator)12
F-TEST (DF denominator)65
p-value0.029703790756373
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation29.3055581217501
Sum Squared Residuals55823.0228937729


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
13781.2802197802198-44.2802197802198
23070.8516483516483-40.8516483516483
34764.423076923077-17.4230769230769
43572.9945054945055-37.9945054945055
53068.8516483516484-38.8516483516484
64372.8516483516484-29.8516483516483
78287.7811355311355-5.78113553113554
84071.6144688644688-31.6144688644688
94777.2811355311355-30.2811355311355
101961.2811355311356-42.2811355311356
115260.9478021978022-8.94780219780221
1213689.947802197802246.0521978021978
138073.9010989010996.09890109890107
144263.4725274725275-21.4725274725275
155457.043956043956-3.04395604395604
166665.61538461538460.384615384615373
178161.472527472527519.5274725274725
186365.4725274725275-2.47252747252747
1913780.402014652014656.5979853479854
207264.2353479853487.76465201465201
2110769.902014652014737.0979853479853
225853.90201465201464.09798534798536
233653.5686813186813-17.5686813186813
245282.5686813186813-30.5686813186813
257966.52197802197812.4780219780219
267756.093406593406620.9065934065934
275449.66483516483524.33516483516485
288458.236263736263825.7637362637363
294854.0934065934066-6.0934065934066
309658.093406593406637.9065934065934
318373.02289377289389.97710622710622
326656.85622710622719.14377289377289
336162.5228937728938-1.52289377289377
345346.52289377289386.47710622710624
353046.1895604395604-16.1895604395604
367475.1895604395604-1.18956043956043
376959.14285714285729.85714285714283
385948.714285714285710.2857142857143
394242.2857142857143-0.285714285714273
406550.857142857142914.1428571428571
417046.714285714285723.2857142857143
4210050.714285714285749.2857142857143
436365.6437728937729-2.64377289377290
4410549.477106227106255.5228937728938
458255.143772893772926.8562271062271
468139.143772893772941.8562271062271
477538.810439560439636.1895604395604
4810267.810439560439534.1895604395605
4912151.763736263736369.2362637362637
509841.335164835164856.6648351648352
517634.906593406593441.0934065934066
527743.47802197802233.521978021978
536339.335164835164823.6648351648352
543743.3351648351648-6.33516483516482
553558.264652014652-23.264652014652
562342.0979853479853-19.0979853479853
574047.764652014652-7.764652014652
582931.764652014652-2.76465201465201
593731.43131868131875.56868131868132
605160.4313186813187-9.43131868131866
612044.3846153846154-24.3846153846154
622833.9560439560439-5.95604395604393
631327.5274725274725-14.5274725274725
642236.0989010989011-14.0989010989011
652531.9560439560440-6.95604395604396
661335.9560439560439-22.9560439560439
671650.8855311355311-34.8855311355311
681334.7188644688645-21.7188644688645
691640.3855311355311-24.3855311355311
701724.3855311355311-7.38553113553113
712524.05219780219780.947802197802195
721453.0521978021978-39.0521978021978
73837.0054945054945-29.0054945054945
74726.5769230769231-19.5769230769231
751020.1483516483516-10.1483516483516
76728.7197802197802-21.7197802197802
771024.5769230769231-14.5769230769231
78328.5769230769231-25.5769230769231


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
160.1240888187327980.2481776374655970.875911181267202
170.1181435484514840.2362870969029680.881856451548516
180.06065997725830550.1213199545166110.939340022741694
190.07037433844219390.1407486768843880.929625661557806
200.03422120112223530.06844240224447060.965778798877765
210.03827910827012360.07655821654024730.961720891729876
220.02015076936460340.04030153872920690.979849230635397
230.09235385692821510.1847077138564300.907646143071785
240.813587119769670.3728257604606590.186412880230329
250.7602165392421930.4795669215156150.239783460757807
260.6993362305471160.6013275389057690.300663769452884
270.6847322086136860.6305355827726280.315267791386314
280.6069594849052260.7860810301895470.393040515094774
290.6657856517552350.6684286964895310.334214348244766
300.605927283475130.788145433049740.39407271652487
310.664440369096670.6711192618066610.335559630903331
320.6127076531692530.7745846936614930.387292346830746
330.628019044003070.7439619119938620.371980955996931
340.6006943368613960.7986113262772080.399305663138604
350.7503545905636950.499290818872610.249645409436305
360.7814381160604390.4371237678791230.218561883939561
370.7841407813190790.4317184373618420.215859218680921
380.815036092740160.3699278145196810.184963907259841
390.9040473587519660.1919052824960690.0959526412480345
400.9204630100931810.1590739798136370.0795369899068185
410.9280336119133470.1439327761733070.0719663880866534
420.9102715968122160.1794568063755680.0897284031877842
430.9290975118074410.1418049763851170.0709024881925586
440.953733675211010.09253264957798110.0462663247889906
450.9299004856320310.1401990287359380.070099514367969
460.9090737469338620.1818525061322770.0909262530661383
470.8790964637081480.2418070725837040.120903536291852
480.8549360761549030.2901278476901950.145063923845097
490.9863763857909340.02724722841813190.0136236142090659
500.9978955031957280.004208993608544540.00210449680427227
510.9993290085966040.001341982806791200.000670991403395602
520.9999643417670987.13164658047125e-053.56582329023562e-05
530.9999899445807352.01108385299669e-051.00554192649835e-05
540.9999828703282583.42593434831371e-051.71296717415685e-05
550.9999706960144195.8607971162252e-052.9303985581126e-05
560.9999342647677940.0001314704644124226.57352322062111e-05
570.9998399750813020.0003200498373968330.000160024918698417
580.999415048672640.001169902654718960.00058495132735948
590.997853514085570.004292971828860080.00214648591443004
600.9997095141476050.0005809717047897110.000290485852394856
610.9983527589958890.003294482008222560.00164724100411128
620.9959989180252440.008002163949512950.00400108197475647


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level130.276595744680851NOK
5% type I error level150.319148936170213NOK
10% type I error level180.382978723404255NOK