However, the investigator might have decided to stop sampling as soon as he encountered 10 males. Conversely, the investigator might have collected data until 3 females were encountered. Alternatively, the investigator might have collected data until the difference between the numbers of males and females was 7, or until the difference was significant at some level. Each set of more extreme outcomes has its own probability, which, along with the probability of the result actually obtained, constitutes P . Hence, P , the outcome of a statistical hypothesis test, depends on results that were not obtained, that is, something that did not happen, and what the intentions of the investigator were.
P is calculated under the assumption that the null hypothesis is true.
Most null hypotheses tested, however, state that some parameter equals zero, or that some set of parameters are all equal. I scanned the results section of each paper, looking for P -values. For each P -value I found, I looked back to see what hypothesis was being tested. Certainly we knew before any data were collected that the null hypotheses being tested were false. The only question was whether or not the sample size was sufficient to detect the difference.