hi,
i'm experimenting with the rpy pkg and for the t.test() i'm noticing a
discrepency w/R.
from venables's intro to R:
A=[79.98,80.04,80.02,80.04,80.03,80.03,80.04,79.97,80.05,80.03,80.02,80.,80.02]
B=[80.02,79.94,79.98,79.97,79.97,80.03,79.95,79.97]
c=r.t_test(A,B, alterntive='two.sided', mu=0, equal='FALSE')
c['p.value']
0.0069393266144479413
c=r.t_test(A,B, alterntive='two.sided', mu=0, equal='TRUE')
c['p.value']
0.0069393266144479413
while in R (variances are statistically equal by var.test and means are not):
> var.test(A,B)
alternative hypothesis: true ratio of variances is not equal to 1
but w/ p-value = 0.3938 you can not accept the alternative
> t.test(A,B,var.equal=T)
Two Sample t-test
data: A and B
t = 3.4722, df = 19, p-value = 0.002551
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
0.01669058 0.06734788
sample estimates:
mean of x mean of y
80.02077 79.97875
thanks,
kevin
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