Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 36729.7493441208 + 1330.07988868374X1[t] + 516.08581468945X2[t] -96.4629479367715X3[t] -0.291806273737337X4[t] -1337.00889635934X5[t] + 2108.20663205954X6[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)36729.749344120825085.8885561.46420.1507760.075388
X11330.07988868374431.6829733.08110.0036760.001838
X2516.085814689451914.1261120.26960.7888050.394403
X3-96.4629479367715552.242343-0.17470.8621950.431097
X4-0.2918062737373370.443026-0.65870.5137920.256896
X5-1337.008896359342698.846809-0.49540.6229630.311481
X62108.206632059542846.9159710.74050.4632030.231601


Multiple Linear Regression - Regression Statistics
Multiple R0.829001263952081
R-squared0.687243095634148
Adjusted R-squared0.641473792556218
F-TEST (value)15.0153716447027
F-TEST (DF numerator)6
F-TEST (DF denominator)41
p-value5.34461952472753e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation47254.460923351
Sum Squared Residuals91552347163.4166


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1210907228616.331011055-17709.3310110555
2120982168864.968849503-47882.9688495031
3176508178496.314671976-1988.31467197596
4179321254183.590290207-74862.5902902075
5123185142078.816246832-18893.8162468316
65274651374.18225461831371.81774538165
7385534270045.798225954115488.201774046
83317042427.9520359793-9257.95203597928
910164581934.676125530119710.3238744699
10149061129250.66933498319810.3306650166
11165446178388.987791434-12942.9877914343
12237213222836.39305941214376.6069405875
13173326193430.465488554-20104.465488554
14133131131461.677736491669.32226351018
15258873261292.924302849-2419.92430284865
16180083180384.676601757-301.676601756683
17324799319642.7312234125156.26877658792
18230964252079.202099863-21115.2020998631
19236785188861.89320821147923.106791789
20135473215998.730977932-80525.7309779319
21202925248010.607998206-45085.6079982057
22215147245085.266721991-29938.2667219912
23344297218123.178775171126173.821224829
24153935138877.03966648815057.9603335121
25132943202261.526341077-69318.526341077
26174724272558.119371602-97834.1193716018
27174415181979.210418988-7564.21041898792
28225548207525.68759571518022.312404285
29223632237246.833749966-13614.8337499658
30124817130120.065994461-5303.06599446053
31221698242447.335022218-20749.3350222179
32210767218157.783544963-7390.78354496344
33170266170399.950227366-133.950227366105
34260561262719.134897056-2158.13489705637
358485395104.8953952407-10251.8953952408
36294424262054.05535793832369.9446420624
3710101192201.4085124528809.59148754803
38215641171875.64782925743765.352170743
39325107197367.94000722127739.05999278
40717636314.5090165926-29138.5090165926
41167542169390.994651203-1848.9946512033
42106408106827.934372354-419.934372354244
4396560127236.888004007-30676.8880040071
44265769229622.76479568336146.2352043167
45269651244748.12944905324902.8705509471
46149112162023.818344044-12911.8183440442
47175824147211.26414116528612.7358588353
48152871147633.028261975237.97173803033


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.7840159675966780.4319680648066440.215984032403322
110.6447049521767120.7105900956465750.355295047823288
120.656105369289740.6877892614205210.34389463071026
130.5915519775390390.8168960449219220.408448022460961
140.5232830958195880.9534338083608230.476716904180412
150.4715591714838880.9431183429677770.528440828516112
160.3652523560426260.7305047120852530.634747643957374
170.2653009724814640.5306019449629270.734699027518536
180.1916144662716450.3832289325432890.808385533728355
190.1890525749584780.3781051499169570.810947425041522
200.3817639041678220.7635278083356450.618236095832178
210.3088399101642230.6176798203284470.691160089835777
220.2698570162668790.5397140325337570.730142983733121
230.8511159075863770.2977681848272460.148884092413623
240.7893164364441080.4213671271117830.210683563555892
250.8205175583895220.3589648832209560.179482441610478
260.9715053824751130.05698923504977420.0284946175248871
270.9497376053537390.1005247892925230.0502623946462613
280.920358551554310.1592828968913790.0796414484456897
290.9167981324089910.1664037351820170.0832018675910087
300.9027099346588930.1945801306822140.0972900653411071
310.9134384579819380.1731230840361230.0865615420180617
320.8569308338054430.2861383323891140.143069166194557
330.8251572082069860.3496855835860280.174842791793014
340.7959038986277430.4081922027445150.204096101372257
350.8900497717067340.2199004565865330.109950228293266
360.8294208974649290.3411582050701410.170579102535071
370.7295438828978410.5409122342043170.270456117102159
380.5871643523279370.8256712953441260.412835647672063


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 level10.0344827586206897OK