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?