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R version 2.9.2 (2009-08-24)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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>
>
> supervisor.table <- read.table('http://www-stat.stanford.edu/~jtaylo/courses/stats191/data/supervisor.table', header=T)
> attach(supervisor.table)
>
> # illustration of "partial" regression coefficients
>
> print(lm(Y ~ X1 + X2 + X3 + X4 + X5 + X6)$coef)
(Intercept) X1 X2 X3 X4 X5
10.78707639 0.61318761 -0.07305014 0.32033212 0.08173213 0.03838145
X6
-0.21705668
> W <- resid(lm(X6 ~ X1 + X2 + X3 + X4 + X5))
> Z <- resid(lm(Y ~ X1 + X2 + X3 + X4 + X5))
> print(summary(lm(Z~W))) # coef for W should match row of X6 above,

Call:
lm(formula = Z ~ W)

Residuals:
Min 1Q Median 3Q Max
-10.9418 -4.3555 0.3158 5.5425 11.5990

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.369e-17 1.170e+00 8.01e-17 1.000
W -2.171e-01 1.615e-01 -1.344 0.190

Residual standard error: 6.406 on 28 degrees of freedom
Multiple R-squared: 0.06059, Adjusted R-squared: 0.02704
F-statistic: 1.806 on 1 and 28 DF, p-value: 0.1898

> # t-statistic, etc. will not because of
> # df, and error sum of squares is not the same
>
>
>
> proc.time()
user system elapsed
0.580 0.040 0.621
R script