How to Test without P-Values?

Authors

  • Hung T. Nguyen Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

Keywords:

Bayes factor, Bayesian tests, calibration of p-values, minimum Bayes factor, Neymann- Pearson tests, P-values, significance tests

Abstract

In view of the p-value crisis in statistics in particular, and in sciences in general, as reported in the news and in the literature during over few decades, this paper aims simply at reminding statisticians of this serious problem (at the heart of statistical inference), as well as providing information for adjusting their teaching and research ”culture”. The main message is this. While the notion of P-values does provide some useful information from the observed data, it is not enough to use it alone to make decisions (in the context of statistical testing of hypotheses). As such, new sound inference procedures are needed for decision-making.

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Published

2019-07-10

How to Cite

Nguyen, H. T. (2019). How to Test without P-Values?. Thailand Statistician, 17(2), i-x. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/202439

Issue

Section

Articles