There is a definition of the P-value in every statistical textbook. Also there is a controversy in one way or another and it has been going on at least for the last 20 years. First I’m going to tell you what a P-value is not. A P-value is not the probability that your theory false. It is not the probability that the null hypothesis is true. It has nothing to do, really, with your hypothesis. It is a sign of how well you’ve done your research, major determinants of the P-value. The P-value being a statistic that you compute from the data in your study. The main influence on the P-value first of all, is the sample size. Second, the reliability of the measures that you use, the quality of your research design, the choice of analysis, you make. The fidelity with which you actually execute your research design, and how well you execute your analysis in the end. So, it all primarily has to do with the quality of the research.
To learn more from Dr. Helena Kraemer listen to the podcast episode below.
Part 1
Part 2
