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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>
> X = c(4,5,2,8,3.4,1)
> Y = c(3,7,5)
>
> # Join the vectors together
>
> Z = c(X, Y)
> dummy = c(1,1,1,1,1,1,0,0,0)
>
> print(summary(lm(Z ~ dummy)))
Call:
lm(formula = Z ~ dummy)
Residuals:
Min 1Q Median 3Q Max
-2.900e+00 -1.900e+00 2.114e-16 1.100e+00 4.100e+00
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.000 1.350 3.702 0.00763 **
dummy -1.100 1.654 -0.665 0.52731
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 2.339 on 7 degrees of freedom
Multiple R-squared: 0.05943, Adjusted R-squared: -0.07494
F-statistic: 0.4423 on 1 and 7 DF, p-value: 0.5273
> print(confint(lm(Z ~ dummy)))
2.5 % 97.5 %
(Intercept) 1.806611 8.193389
dummy -5.011087 2.811087
> print(t.test(X,Y,var.equal=T))
Two Sample t-test
data: X and Y
t = -0.6651, df = 7, p-value = 0.5273
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-5.011087 2.811087
sample estimates:
mean of x mean of y
3.9 5.0
>
>
> proc.time()
user system elapsed
0.540 0.032 0.560
R script