Hello,
On 8/16/09, Ted Harding <ted.hard...@manchester.ac.uk> wrote:
> I don't know about *compelling* reasons! But (as a general rule)
> if the Alternative Hyptohesis is stated, then the Null Hypothesis
> is simply its negation. So, in your example, you can infer
>
> H0: true tau equals 0
> Ha: true tau is not equal to 0.
>
Oh, I had a slightly different H0 in mind. In the given example,
cor.test(..., met="kendall") would test "H0: x and y are independent",
but cor.test(..., met="pearson") would test: "H0: x and y are not
correlated (or `are linearly independent')" .
To take a different example, a test of normality.
> shapiro.test(mtcars$wt)
Shapiro-Wilk normality test
data: mtcars$wt
W = 0.9433, p-value = 0.09265
Here both "H0: x is normal" and "Ha: x is not normal" are missing. At
least to beginners, these things are not always perfectly clear (even
after reading the documentation), and when interpreting the results it
can prove useful to have on-screen information about the null.
Thank you for answering
Liviu
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