心理統計の新しい展開と今後の統計教育

抄録

In this article, I have selected and will comment on three topics from the papers in this special issue: power analysis, Bayesian hypothesis testing, and Bayesian statistical modeling. The major problem in power analysis is the quantitative evaluation of effect size, and this problem is shared in the estimation of effect size. Bayesian hypothesis testing is theoretically superior to classical null hypothesis testing. However, setting prior distributions properly continues to be difficult to overcome. Bayesian statistical modeling changes the role of statistics in psychological research and is promising in many aspects. However, the ease of computation can mask the necessity of careful thinking in modeling, which includes setting prior distributions. I also will discuss future statistics education in the era of rapid developments in methodology, as documented in this special issue.