# Fallacy in p-value definition

I have two more questions. Why Statsoft's textbook says that

the p-value represents the probability of error that is involved in accepting our observed result as valid

whereas Wikipedia gives a slightly different definition:

p-value is the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true

Wikipedia warns us against confusing Fisher's p-value criteria with Pearson's Type I error (probability of taking a wrong decision). I read that statsoft's definition falls into the Type I fallacy. Am I wrong? Can you explain how these definitions related?

• The link to the textbook is dead. That is precisely why it is always a good idea to include a full reference. Jan 4, 2021 at 8:47

The StatSoft definition is incorrect. (I know, a short answer, but sometimes there is no long answer).

• It's also really only centered on two population t-tests somehow. This whole explanation seems to be wrong and misleading. In fact I would stop using that textbook and probably the software as well. ugh
– IMA
Jun 5, 2013 at 15:44