Dear friends,
The P is the probability of getting a value of a test statistic equal to or
greater than the one observed in your data, if it is a random pick from the
distribution of the test statistic that would be created if a specified null
hypothesis were true. So, in the situation where the means of two
distributions are being compared, a t statistic might be calculated. If the
null hypothesis is that the distributions have an identical mean, the t
statistic comes from a distribution of t with mean of zero. In such a
distribution, there is a particular probability (P) that any given value of
t will be equaled or exceeded if you pick t values at random. It is not to
be confused with the probability you choose to decide to reject the null
hypothesis (i.e. alpha, which is then the probability of rejecting the null
hypothesis incorrectly - you think it is wrong when it is true, i.e. the
probability of Type I error).
But....... I think this is very dificult to teach for young students (using
these words!). So, does anyone can send me a suggestion? I would like to use
a more simple explanation!
For instance, in the book "The truth about Science" (p.101) I read:
"A p-value of 0.80 means that
there is an 80% chance of finding the data
when the population are exactly the same".
So, for many students this statement means like "the P value is the
probability of Ho is correct" !
I would like to avoid a simple explanation to my kidos like "just look if
the P value is above or below 0.05 to reject or accept the Ho" :(
Thanks for any help !!!
Voltolini
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Prof. J. C. VOLTOLINI
Grupo de Estudos em Ecologia de Mamiferos (ECOMAM)
Universidade de Taubate, Departamento de Biologia
Praca Marcelino Monteiro 63, Bom Conselho.
Taubate, SP. CEP 12030-010. BRASIL.
Tel: 0XX12 - 2254165 (Lab. Zool.) ou 2254277 (Depto. Biol.)
E-Mail: [EMAIL PROTECTED]
http://jcvoltol.sites.uol.com.br/personalidades/
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
"Tutto di noi è un angelo con un'ala e
possiamo volare soltanto se ci abbracciamo"
.
.
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