Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 42.6772231284869 -7.03032756296926X[t] + 0.238951819573219Y1[t] + 0.0273389519798325Y2[t] + 0.402193805311858Y3[t] + 35.1639106297578O1[t] + 46.4502697020821O2[t] + 48.3685051126588O3[t] -11.0549275547205M1[t] -13.5843855756605M2[t] -8.58775754021385M3[t] -20.1079767133796M4[t] -20.0203484270343M5[t] -19.5705285141657M6[t] -11.6321889599801M7[t] -26.7128084146589M8[t] -13.1819891149909M9[t] -20.6649646317261M10[t] -9.85178558791026M11[t] + 0.183754648718384t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)42.67722312848698.7975854.8516e-063e-06
X-7.030327562969263.552399-1.9790.0510490.025525
Y10.2389518195732190.0827882.88630.004940.00247
Y20.02733895197983250.0831310.32890.7430660.371533
Y30.4021938053118580.0807344.98173e-062e-06
O135.163910629757810.1778733.45490.0008610.000431
O246.450269702082110.6064834.37943.4e-051.7e-05
O348.368505112658810.1296724.77497e-064e-06
M1-11.05492755472054.699848-2.35220.0209750.010487
M2-13.58438557566054.758527-2.85470.005410.002705
M3-8.587757540213854.701252-1.82670.0712560.035628
M4-20.10797671337964.662171-4.3134.3e-052.2e-05
M5-20.02034842703434.654534-4.30134.5e-052.3e-05
M6-19.57052851416574.751112-4.11918.8e-054.4e-05
M7-11.63218895998014.72272-2.4630.0157940.007897
M8-26.71280841465894.617594-5.78500
M9-13.18198911499094.73033-2.78670.0065660.003283
M10-20.66496463172615.198466-3.97520.0001477.4e-05
M11-9.851785587910264.740023-2.07840.0406860.020343
t0.1837546487183840.0616732.97950.0037630.001882


Multiple Linear Regression - Regression Statistics
Multiple R0.8889895636866
R-squared0.79030244434369
Adjusted R-squared0.743428873079338
F-TEST (value)16.8602993760949
F-TEST (DF numerator)19
F-TEST (DF denominator)85
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation9.36884861575549
Sum Squared Residuals7460.9025727202


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1102.1880309102.226401502267-0.0383706022670232
2110.3672031100.4950984448179.87210465518332
396.8602511109.663025019250-12.8027739192496
494.194458390.56591492534093.62854337465911
599.5162196193.12064829953646.39557131046357
694.0633348789.52057500509034.54275986490975
797.554147695.41301850394552.14112909605448
878.1506242283.3415930297799-5.19096880977987
981.243464390.3219784584722-9.0785141584722
1092.3626246584.63530861680487.72731603319523
1196.0632437190.56976400886655.49347970113348
12114.0523777103.03748121529011.0148964847095
13110.6616666101.0380730685619.62359353143855
14104.917194999.862323241415.05487165858988
1590.00187193110.812473726136-20.8106017961359
1695.700806794.39119480250691.30961189749312
1786.0274115793.3061883395213-7.27877676952126
1884.8528766885.7852399345976-0.932363254597588
19100.0432895.65429266481334.38898733518674
2080.9171382380.46451222164170.452626008358317
2174.0653970989.5517588427103-15.4863617527103
2277.3028136986.201899406129-8.89908571612898
2397.2304324990.09268452453477.13774796546531
2490.75515676102.222745268043-11.4675885080425
25100.561445591.6511625592988.91028294070206
2692.0129326799.4864273084972-7.47349463849718
2799.24012138100.287905167960-1.04778378795975
28105.867275594.38871173873511.478563761265
2990.992046393.0030900696017-2.01104376960173
3093.3062442393.17011152451150.136132705488542
3191.17419413104.103914690765-12.9297205607647
3277.3329503982.7781353432341-5.44518495323413
3391.127772194.0577869712-2.93001487120001
3485.0124994388.8189614106923-3.8064619806923
3583.9039024293.1649130498042-9.26101062980418
36104.8626302108.316558704995-3.45392850499472
37110.903910899.96367927187510.9402315281250
3895.4371437399.1886696939024-3.75152596390237
39111.6238727109.2678730043292.35599969567055
40108.8925403103.8061772514635.08636304853713
4196.1751168297.6467936419532-1.47167682195316
42101.9740205101.6770470773820.29697342261759
4399.11953031109.738593864798-10.6190635547978
4486.7815814789.2033104400426-2.42172897004263
45118.4195003102.22395343077416.1955468692255
46118.7441447100.99930597208817.7448387279119
47106.5296192107.976514984649-1.44689578464920
48134.7772694127.8268225318776.95044686812313
49104.6778714123.502114680341-18.8242432803408
50105.2954304109.823760049398-4.52832964939781
51139.4139849125.68985350881913.7241313911809
52103.6060491110.417171659984-6.81112255998436
5399.78182974103.313327107788-3.53149736778837
54103.4610301115.776417323618-12.3153872236181
55120.0594945110.2713830379119.78811146208948
5696.7137716897.903259647672-1.18948796767198
57107.1308929107.972866863431-0.841973963430958
58105.3608372109.200388029907-3.83955082990689
59111.6942359110.6696517702501.02458412974980
60132.0519998126.3598793064095.69212049359073
61126.8037879119.8144741720866.9893137279144
62154.4824253154.4824253-1.10458517332823e-15
63141.5570984139.1570440419122.40005435808808
64109.9506882123.377955759733-13.4272675597327
65127.904198126.8757410776391.02845692236082
66133.0888617125.7367669321387.35209476786163
67120.0796299122.876673711739-2.79704381173873
68117.5557142112.2337629930105.32195120698979
69143.0362309127.07482355172315.9614073482774
70159.982927159.9829275.22368606703516e-15
71128.5991124128.2605422221150.338570177885233
72149.7373327141.5082737387058.2290589612951
73126.8169313141.645972627557-14.8290413275566
74140.9639674121.77891860600119.1850487939986
75137.6691981138.214802814574-0.545604714573759
76117.9402337117.2593688530710.680864846928982
77122.3095247118.4162545897253.89327011027469
78127.7804207118.2293741732729.55104652672794
79136.1677176119.84333350000916.3243840999913
80116.2405856108.8574988864407.38308671356037
81123.1576893120.2401087724452.91758052755468
82116.3400234117.422274371368-1.08225097136772
83108.6119282118.964651709717-10.3527235097168
84125.8982264129.749177954655-3.85095155465549
85112.8003105120.055296441994-7.25498594199434
86107.5182447111.944219492949-4.42597479294927
87135.0955413122.45680170208612.6387395979136
88115.5096488112.2976755983833.21197320161680
89115.8640759106.5184941260789.34558177392226
90104.5883906117.792719773344-13.2043291733439
91163.7213386163.72133863.38704758684472e-16
92113.4482275114.420177167808-0.971949667807623
9398.0428844113.203521790734-15.1606373907343
94116.7868521124.631657363011-7.84480526301127
95126.5330444119.4667964500647.06624794993638
96113.0336597126.147713940026-13.1140542400258
97124.3392163119.8559968760214.48321942397876
98109.8298759123.762575963025-13.9327000630252
99124.4434777120.3556385249344.08783917506596
100111.5039454116.661475410783-5.15753001078309
101102.0350019108.404887288157-6.36988538815682
102116.8726598112.2995874360464.57307236395417
103112.2073122118.504096266021-6.29678406602085
104101.151390299.08973376037222.06165643962777
105124.4255108116.0025434085108.42296739149013


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
230.3529103287541000.7058206575082010.6470896712459
240.6861453726939660.6277092546120670.313854627306034
250.5623896080122110.8752207839755770.437610391987789
260.5064512366851970.9870975266296060.493548763314803
270.4700616483766340.9401232967532680.529938351623366
280.6399835643040860.7200328713918290.360016435695914
290.5416397179346720.9167205641306550.458360282065328
300.4889622267130760.9779244534261530.511037773286924
310.4282229337657790.8564458675315570.571777066234221
320.346830844745970.693661689491940.65316915525403
330.4389103150738980.8778206301477970.561089684926102
340.3618226677808590.7236453355617170.638177332219141
350.3550664874136160.7101329748272310.644933512586384
360.3027948005065550.6055896010131110.697205199493445
370.2898499652932290.5796999305864580.710150034706771
380.2328506375778680.4657012751557370.767149362422131
390.3344641605756030.6689283211512050.665535839424397
400.2987171577643620.5974343155287240.701282842235638
410.2467773563270450.493554712654090.753222643672955
420.2010296499684240.4020592999368480.798970350031576
430.2067374337548520.4134748675097040.793262566245148
440.1855944439115170.3711888878230340.814405556088483
450.4374209188611370.8748418377222750.562579081138863
460.5775691678981360.8448616642037290.422430832101864
470.5176143787227560.9647712425544880.482385621277244
480.4712206868986090.9424413737972180.528779313101391
490.690959765131520.618080469736960.30904023486848
500.6460100698280440.7079798603439120.353989930171956
510.7271310351667960.5457379296664080.272868964833204
520.6952490794258260.6095018411483470.304750920574174
530.6500157915070660.6999684169858690.349984208492934
540.7404781344285460.5190437311429090.259521865571454
550.7255357596034120.5489284807931770.274464240396589
560.717695138021780.564609723956440.28230486197822
570.733625945803630.5327481083927410.266374054196371
580.7084182769937470.5831634460125070.291581723006253
590.6932709506737510.6134580986524980.306729049326249
600.6472254620962050.705549075807590.352774537903795
610.586997323510.826005352980.41300267649
620.5136097099258970.9727805801482050.486390290074103
630.4567976773837850.9135953547675690.543202322616215
640.4574237155850320.9148474311700640.542576284414968
650.3972197219772360.7944394439544730.602780278022764
660.3491942159076920.6983884318153830.650805784092308
670.3180887802655850.636177560531170.681911219734415
680.3303690490992560.6607380981985120.669630950900744
690.3073948395088770.6147896790177550.692605160491123
700.2390862308891190.4781724617782380.760913769110881
710.1915034229069620.3830068458139240.808496577093038
720.2345824233466920.4691648466933850.765417576653308
730.2271934077061590.4543868154123190.77280659229384
740.5564211214786390.8871577570427230.443578878521362
750.4620077171635150.9240154343270290.537992282836485
760.3759528528982510.7519057057965020.624047147101749
770.2815644306191340.5631288612382680.718435569380866
780.2353725523650920.4707451047301850.764627447634908
790.3498619498997680.6997238997995360.650138050100232
800.2853118471110560.5706236942221130.714688152888943
810.2007499294847370.4014998589694740.799250070515263
820.119775330853520.239550661707040.88022466914648


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