Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 572.83488800214 -0.000146008298080128X1[t] -0.630378069393324X2[t] + 0.450256139727406X3[t] + 0.0365924346513837X4[t] -0.00809979353242481`X5 `[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)572.8348880021439.59558914.467100
X1-0.0001460082980801280.00019-0.76660.450810.225405
X2-0.6303780693933240.188914-3.33690.0027530.001376
X30.4502561397274060.0003891157.104700
X40.03659243465138370.081580.44850.6577820.328891
`X5 `-0.008099793532424810.008937-0.90630.3737670.186884


Multiple Linear Regression - Regression Statistics
Multiple R0.999992331728976
R-squared0.999984663516755
Adjusted R-squared0.999981468416079
F-TEST (value)312974.383256124
F-TEST (DF numerator)5
F-TEST (DF denominator)24
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation28.4532671102599
Sum Squared Residuals19430.1218219471


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
13390733905.43792950971.56207049032452
23598136006.5233704825-25.523370482484
33658836591.1327598573-3.13275985730758
41696716929.342333514237.6576664858072
52533325314.982547344918.0174526551017
62102721006.819668209320.1803317907115
72111421168.1865008444-54.1865008443737
82877728757.930538358519.0694616414676
93561235596.932310113715.0676898863351
102418324169.804240138713.1957598612586
112226222262.6935562304-0.693556230366313
122063720660.5363198477-23.5363198477489
132994830002.2872490294-54.2872490293551
142209322110.5563583762-17.5563583762373
153699736981.618581190715.3814188092548
163108931106.9257619196-17.9257619196433
171947719454.349199247922.6508007521272
183130131342.6656590804-41.6656590803559
191849718494.85325842332.14674157672846
203014230152.6984426177-10.6984426176812
212132621346.42326735-20.4232673500205
221677916791.0311509395-12.0311509395281
233806838068.9558884401-0.955888440056607
242970729721.7227234828-14.7227234827574
253501635011.46580720554.53419279454071
262613126099.759852860431.240147139598
272925129210.823035526940.1769644731229
282285522857.1248395458-2.12483954579336
293180631753.59034631152.409653688992
303412434117.82650400176.17349599833911


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.5922723022284290.8154553955431430.407727697771571
100.422459827869470.8449196557389390.57754017213053
110.332211810088410.664423620176820.66778818991159
120.2085227796640310.4170455593280620.791477220335969
130.839742333248470.3205153335030610.16025766675153
140.7866257803346180.4267484393307640.213374219665382
150.751121546976060.497756906047880.24887845302394
160.869942492366630.260115015266740.13005750763337
170.8911524542755230.2176950914489530.108847545724477
180.8807090977252630.2385818045494730.119290902274737
190.8567662972989460.2864674054021070.143233702701054
200.735935020458020.528129959083960.26406497954198
210.6982142251892320.6035715496215360.301785774810768


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