Dear Yuri,<div><br></div><div>it strictly depends by:</div><div><ul><li>the number of samples (more than 30?)</li><li>the number of factors (2 or more?)</li><li>are the data from each factor becoming from the same samples? (dependent vs. independent factors) </li>
</ul></div><div>Let me know, I will tell you which one is better to use. ;)</div><div><br></div><div>Bye,</div><div>Michele Filannino.<br><br><font color="#666666">CDT PhD student in Computer Science<br>Room IT301 - IT Building<br>
The University of Manchester<br><a href="mailto:filannim@cs.manchester.ac.uk" target="_blank">filannim@cs.manchester.ac.uk</a></font></div><div><br><div class="gmail_quote">On Tue, Aug 7, 2012 at 11:28 AM, Yuri Tambovtsev <span dir="ltr"><<a href="mailto:yutamb@mail.ru" target="_blank">yutamb@mail.ru</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><u></u>
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<div><font face="Arial">Dear Corpora members, I wonder if you could advise
me which math. statistics criteria is more reliable to state the difference
between two samples, that is, t-test or chi-square? I used t-test to see the
difference in the occurrence of all colours in the texts of 26 British and
American writers. Should I also use the chi-square criterion to substantiate the
difference between two samples or t-test is reliable enough? Looking forward to
hearing from you to <a href="mailto:yutamb@mail.ru" target="_blank">yutamb@mail.ru</a>
Remain yours sincerely Yuri Tambovtsev, Novosibirsk,
Russia</font></div></div>
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