Multiple Linear Regression - Estimated Regression Equation
births[t] = + 9430.3111111111 + 286.706944444440difference[t] + 99.161855158722M1[t] -638.203273809523M2[t] -284.711259920635M3[t] -37.5551587301577M4[t] -920.277430555554M5[t] + 41.0002976190488M6[t] -338.555307539682M7[t] -164.444246031745M8[t] -214.333184523809M9[t] + 355.611210317461M10[t] + 228.722271825397M11[t] + 5.22227182539697t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)9430.3111111111140.71317167.01800
difference286.706944444440134.5833562.13030.0371850.018593
M199.161855158722158.5738740.62530.5340830.267042
M2-638.203273809523158.462983-4.02750.0001597.9e-05
M3-284.711259920635158.413321-1.79730.0772430.038622
M4-37.5551587301577166.197782-0.2260.8219830.410991
M5-920.277430555554165.759024-5.55191e-060
M641.0002976190488165.3778250.24790.805030.402515
M7-338.555307539682165.054585-2.05120.0445520.022276
M8-164.444246031745164.789644-0.99790.3222680.161134
M9-214.333184523809164.583284-1.30230.1977170.098859
M10355.611210317461164.4357252.16260.0345010.01725
M11228.722271825397164.3471261.39170.1690670.084533
t5.222271825396973.1160741.67590.0988740.049437


Multiple Linear Regression - Regression Statistics
Multiple R0.857999753809147
R-squared0.736163577536557
Adjusted R-squared0.67993614324107
F-TEST (value)13.0926048246813
F-TEST (DF numerator)13
F-TEST (DF denominator)61
p-value3.89466237038505e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation284.606401731326
Sum Squared Residuals4941049.03829363


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
197009534.69523809529165.304761904713
290818802.55238095238278.447619047622
390849161.26666666666-77.2666666666633
497439413.64503968254329.354960317462
585878536.1450396825450.854960317464
697319502.64503968254228.354960317463
795639128.3117063492434.688293650796
899989307.64503968254690.354960317463
994379262.97837301587174.02162698413
10100389838.14503968254199.854960317462
1199189716.47837301587201.521626984129
1292529492.97837301587-240.978373015871
1397379597.36249999999139.637500000010
1490358865.21964285714169.780357142859
1591339223.93392857143-90.9339285714269
1694879476.312301587310.6876984126990
1787008598.8123015873101.187698412698
1896279565.312301587361.6876984126988
1989479190.97896825397-243.978968253968
2092839370.3123015873-87.312301587301
2188299325.64563492063-496.645634920635
2299479900.812301587346.1876984126991
2396289779.14563492063-151.145634920634
2493189555.64563492063-237.645634920634
2596059660.02976190475-55.0297619047533
2686408927.8869047619-287.886904761905
2792149286.60119047619-72.6011904761905
2895679538.9795634920628.0204365079354
2985478661.47956349206-114.479563492065
3091859627.97956349206-442.979563492065
3194709253.64623015873216.353769841269
3291239432.97956349206-309.979563492065
3392789388.3128968254-110.312896825398
34101709963.47956349206206.520436507935
3594349841.8128968254-407.812896825398
3696559618.312896825436.6871031746021
3794299722.69702380952-293.697023809517
3887398990.55416666667-251.554166666668
3995529349.26845238095202.731547619046
4096879888.35376984127-201.353769841269
4190199010.853769841278.1462301587311
4296729977.35376984127-305.353769841269
4392069603.02043650794-397.020436507935
4490699782.35376984127-713.353769841269
4597889737.687103174650.3128968253978
461031210312.8537698413-0.853769841268381
471010510191.1871031746-86.187103174602
4898639967.6871031746-104.687103174602
49965610072.0712301587-416.071230158721
5092959339.92837301587-44.9283730158724
5199469698.64265873016247.357341269842
5297019951.02103174603-250.021031746032
5390499073.52103174603-24.5210317460325
541019010040.0210317460149.978968253968
5597069665.687698412740.3123015873011
5697659845.02103174603-80.0210317460321
5798939800.3543650793792.6456349206342
58999410375.5210317460-381.521031746032
591043310253.8543650794179.145634920634
601007310030.354365079442.6456349206345
611011210134.7384920635-22.7384920634845
6292669402.59563492064-136.595634920636
6398209761.3099206349258.6900793650783
641009710013.688293650883.3117063492042
6591159136.1882936508-21.1882936507961
661041110102.6882936508308.311706349204
6796789728.35496031746-50.3549603174625
68104089907.6882936508500.311706349204
69101539863.02162698413289.978373015871
701036810438.1882936508-70.1882936507957
711058110316.5216269841264.478373015871
721059710093.0216269841503.97837301587
731068010197.4057539682482.594246031752
7497389465.2628968254272.737103174600
7595569823.97718253969-267.977182539686


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
170.1287040941606900.2574081883213800.87129590583931
180.0585261049506310.1170522099012620.941473895049369
190.3323676144693850.664735228938770.667632385530615
200.5508841074487160.8982317851025680.449115892551284
210.5867566713536340.8264866572927320.413243328646366
220.5134490185043250.973101962991350.486550981495675
230.4078719815518020.8157439631036030.592128018448198
240.3705938047691510.7411876095383030.629406195230849
250.3190365610081330.6380731220162660.680963438991867
260.2495087175416660.4990174350833320.750491282458334
270.2804863227684900.5609726455369810.71951367723151
280.2423723346773510.4847446693547020.757627665322649
290.1824973350995240.3649946701990470.817502664900476
300.1977471431570210.3954942863140410.80225285684298
310.2999590302742430.5999180605484850.700040969725757
320.2877078526017510.5754157052035030.712292147398249
330.2887685777805150.577537155561030.711231422219485
340.3824245330037430.7648490660074870.617575466996257
350.3742070999535860.7484141999071720.625792900046414
360.442915661496230.885831322992460.55708433850377
370.3848646290269030.7697292580538050.615135370973097
380.3590140372140790.7180280744281580.640985962785921
390.4463073937828480.8926147875656970.553692606217152
400.3751816315465140.7503632630930280.624818368453486
410.3643615403844410.7287230807688820.635638459615559
420.3164595305081560.6329190610163110.683540469491844
430.2823692156678270.5647384313356540.717630784332173
440.54553715960920.90892568078160.4544628403908
450.5628523188879680.8742953622240640.437147681112032
460.6271859254952320.7456281490095360.372814074504768
470.5644365603499070.8711268793001860.435563439650093
480.5031674507355860.9936650985288270.496832549264414
490.5594251094923560.8811497810152880.440574890507644
500.483790186403130.967580372806260.51620981359687
510.7830174292104450.433965141579110.216982570789555
520.7053026668914520.5893946662170950.294697333108548
530.6481885209959240.7036229580081520.351811479004076
540.5846574128348710.8306851743302580.415342587165129
550.5803661153879480.8392677692241040.419633884612052
560.5584800634487710.8830398731024570.441519936551229
570.4293484806326750.858696961265350.570651519367325
580.293459673420110.586919346840220.70654032657989


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