Regression Interpretation

Number CarsHousehold SizeHousehold-size cubedPredicted Cars 1111.24 2281.59 23271.96 24642.38 35cxxv2.84 the population regression model is Y^=B0+B1X1+B2X2 heavyset issue Regression Statistics Multiple R (Correlation Coefficient)0.895828018Correlation between Xs & Ys R substantive0.80250783780.25% of the y ^ and the in reality y is due to the regressors X1 and X2. The remain 20% is due to something else outside of those variables Adjusted R lame (correlation w/removing the most extreme values)0.605015674=r-square-(1-r-square)*(df-1)*(n-df)df=total number of indepent viariables streamer misplay (Estimated Standard Deviation of actual error)0.444400903 Observations (N)5 analysis of variance analysis of variancess=residual integrality of squares + regression sum of squares dfSS (Sum of substantives)MSFSignificance F Regression ((R Square % of the df values)21.6050156740.8025078374.0634920630.197492163 Residual (is the difference btwn the actual and estimated)(The error)20.3949843260.

197492163 totality42 r-square=1-residualss/TotalSS Coefficients (Betas)Standard Errort Stat (Ho:Bi=0)(If the B was actually 0 and irrelevantP-value (P-value associated to the T-value)Lower 95% fastness 95%Lower 95.0%Upper 95.0% Intercept B00.8965517240.7643980641.1728859180.361624318-2.3923876914.185491139-2.3923876914.185491139 X Variable 10.336468130.4227037640.795990380.509506953-1.4822793752.155215634-1.4822793752.155215634 X Variable 20.0020898640.0131137940.1593638150.888021498-0.0543342350.058513964-0.0543342350.058513964 Y^=B0+B1X1+B2X2If you want to get a full essay, order it on our web site: B! estEssayCheap.com

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