this is refreshing news via nature.com in the morning. the American Statistical Association (ASA) warns that the P value “CANNOT determine whether a hypothesis is true or whether results are important.” (emphasis added).
a 6-principle list that addresses misconceptions and misuse of the p-value, can be found in the ASA statement:
- P-values can indicate how incompatible the data are with a specified statistical model.
- P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
- Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
- Proper inference requires full reporting and transparency.
- A p-value, or statistical significance, does not measure the size of an effect or the importance of a result.
- By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis.
the press release statement goes here:
good to take note for those of us into educational research, and have the tendency to rely on quanti methods. and its our duty to correct the misconceptions of non-researchers on the use of p-value too.