Comparing two models

# Comparing two models - Basic Model(percent~x y...

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Basic Model (percent~x+y+z) #Comparison of Models #Basic Model (x, y, z) basic <- lm ( percent ~ x + y + z ) summary ( basic ) Call: lm(formula = percent ~ x + y + z) Residuals: Min 1Q Median 3Q Max -22.6733 -2.8960 -0.6683 2.6733 20.6683 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.7624 0.4017 9.365 < 2e-16 *** x 13.3416 0.4017 33.209 < 2e-16 *** y -1.4356 0.4017 -3.574 0.000373 *** z 5.5693 0.4017 13.863 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 5.71 on 804 degrees of freedom Multiple R-squared: 0.6193, Adjusted R-squared: 0.6179 F-statistic: 435.9 on 3 and 804 DF, p-value: < 2.2e-16 Diagnostic #Diagnostic plot ( basic \$ fit basic \$ res xlab = "Fitted" ylab = "Residuals" main = "Residuals-Fitted plot for Basic Model" )

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decompressor are needed to see this picture. #jittered plot
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Comparing two models - Basic Model(percent~x y...

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