[R] log-normal distribution and shapiro test

[Siegfried Gonzi]

Hello:

Yes I know that sort of questions comes up quite often. But with all due 
respect I din't find how to perform what I want. I am searching archives 
and bowsing manuals but it isn't there, though, it is a ridiculous 
simple task for the experienced R user.

I have data and can do the following with them:

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hist(y, prob=TRUE)
lines(density(y,bw=0.03)
==

The result actually is a nice histogram superimposed by a line plot.

The histogram is a bit skewed to the left. My assumption actually is 
that a log-normal transformation would cure the problem. But how the 
hell can one plot such a density function or Gaussian function which has 
logarithmic scales on x axis.

For example I tried:

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plot(hist(y),log="x")

or

plot(hist(log10(y)),log="x")
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But with no avail. I want  my axis like: 1,10,100



What would be other methods to test whether the data are logaritmically 
distributed.

A last question to the Shapiro-Wilk test. Were can I get critical 
parameters? I mean I get for my distribution: W=0.9686, p-value=6.887e-07.
What does that mean? Yes I have got some books about statics, but none 
of them says what one should do with the values then. The logaritmic 
transformation "shapiro.test(log10(y))" says: W=0.9773, p-value= 2.512e-05.

Sorry for disturbing you. Although, it is really no homework. I need it 
for my Phd in physics; after a lengthy computation on the computer I 
would like to go to see whether the outputs are log-normal or normal 
distributed.

Regards,
Siegfried Gonzi
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University of Graz
Institute for Physics
Tel.: ++43-316-380-8620
==