Multiple Linear Regression - Estimated Regression Equation
SWS[t] = + 12.3197087181946 + 0.142634167491983PS[t] + 0.0110188228044140LS[t] + 0.00358575159323686BW[t] -0.00147763369106797BRW[t] -0.0142418480170465GT[t] + 1.51015954701529PI[t] + 0.137314401734720SEI[t] -2.67140908301206ODI[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)12.31970871819462.2394185.50135e-062e-06
PS0.1426341674919830.496630.28720.7758080.387904
LS0.01101882280441400.0422040.26110.7956990.39785
BW0.003585751593236860.0053470.67060.5072570.253628
BRW-0.001477633691067970.003185-0.46390.6458610.32293
GT-0.01424184801704650.006737-2.11410.0423940.021197
PI1.510159547015291.0784341.40030.1710380.085519
SEI0.1373144017347200.6386240.2150.8311190.41556
ODI-2.671409083012061.489998-1.79290.0824480.041224


Multiple Linear Regression - Regression Statistics
Multiple R0.760338768848172
R-squared0.578115043413554
Adjusted R-squared0.472643804266942
F-TEST (value)5.48125771623805
F-TEST (DF numerator)8
F-TEST (DF denominator)32
p-value0.000214898271983843
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.71971430821945
Sum Squared Residuals236.699069386675


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
16.38.70380330205908-2.40380330205908
22.11.312611576207340.787388423792664
39.15.830382102803543.26961789719646
415.811.56257897201784.23742102798217
55.23.580084702072461.61991529792754
610.911.3318671598544-0.431867159854397
78.38.30765149375464-0.00765149375463509
8118.422190849925652.57780915007436
93.24.67081779500448-1.47081779500448
106.311.0342093697054-4.73420936970541
118.610.3978242579169-1.7978242579169
126.610.3222369535801-3.72223695358011
139.58.84190242764450.6580975723555
143.35.31318709479185-2.01318709479185
151111.9436962615884-0.943696261588399
164.77.64571042416454-2.94571042416454
1710.412.1733990623514-1.77339906235140
187.48.82182024493103-1.42182024493103
192.13.93607180858023-1.83607180858023
207.79.38144702614722-1.68144702614722
2117.911.13306771446336.76693228553672
226.17.13792748862824-1.03792748862825
2311.910.43301501615431.46698498384567
2410.810.36316909599410.43683090400588
2513.813.48566309217520.314336907824777
2614.311.60729132306892.69270867693112
27106.019734631099993.98026536890001
2811.910.28136272309181.6186372769082
296.57.57715903464924-1.07715903464924
307.57.076330330899320.42366966910068
3110.69.0950295126741.50497048732599
327.410.9462168724777-3.54621687247767
338.48.324083319060810.0759166809391907
345.77.2574395755035-1.55743957550350
354.96.02548152863396-1.12548152863396
363.25.29589427038155-2.09589427038155
37119.657041783601541.34295821639846
384.96.26785977209513-1.36785977209513
3913.211.51974394976901.68025605023102
409.75.375219488726754.32478051127325
4112.813.5877765917507-0.787776591750676


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.9382467970348840.1235064059302330.0617532029651163
130.9262008726669330.1475982546661340.073799127333067
140.8968481684597030.2063036630805950.103151831540297
150.8456018038511580.3087963922976840.154398196148842
160.895914612643150.2081707747137010.104085387356850
170.9299183035883230.1401633928233550.0700816964116775
180.9046548473339770.1906903053320470.0953451526660234
190.9027426696962410.1945146606075190.0972573303037594
200.8895601787161220.2208796425677560.110439821283878
210.9716686702834010.05666265943319780.0283313297165989
220.9462627515868480.1074744968263040.0537372484131521
230.9104758342908520.1790483314182960.0895241657091479
240.8877081492149810.2245837015700380.112291850785019
250.8133913781920870.3732172436158270.186608621807913
260.7301305630789310.5397388738421380.269869436921069
270.8494477509281490.3011044981437030.150552249071851
280.7319146392270260.5361707215459480.268085360772974
290.57232448086220.85535103827560.4276755191378


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 level10.0555555555555556OK