Some good sense about p value

http://blogs.plos.org/absolutely-maybe/2016/04/25/5-tips-for-avoiding-p-value-potholes/

http://bitesizebio.com/26743/3-common-myths-about-p-value-alternatively-never-ever-rely-on-it-for-data-interpretation/


Null Hypothesis Significance Testing (NHST) is a statistical method for testing whether the factor we are talking about has the effect on our observation. For example, a t test or an ANOVA test for comparing the means is a good example of NHST. It probably the most common statistical testing used in HCI.

P-value is a measure of how much evidence we have against the null hypothesis. The most important thing to remember about p-value is that it is used to test hypotheses. It is a measure of how much evidence we have against the null hypothesis, which is the hypothesis of no change or no difference.