# Guest Post: “The fast guide to statistical testing with JASP”

This is a guest post by Cole Davis, who introduces his new course book “The fast guide to statistical testing with JASP” (for an overview of JASP-related teaching materials click here or here).

Cole Davis:

This relatively short book, published in 2023, is part of the Vor Press ‘Statistics without Mathematics’ series. It contains no statistical formulae.

Each test, in classical mode, is accompanied by a Bayesian result for the same data.

In the chapter on Bayesian statistics, clear guidance is given on how to test hypotheses in a straightforward manner.

The original Jeffreys and Raftery interpretations are presented with guidance on how to use the report bandings.

The original interpretations are discussed, with an adapted reporting table suggested. This table appears at different stages of the book for convenience of use.

Some guidance is offered about the use of classical and Bayesian tests, but no strong theoretical claims are made.

The book has an eclectic style and does not seek to differentiate between the Fisher and Neyman-Pearson schools of thought. So for some tutors the coverage of classical statistics will be therefore be “wrong”, not to mention the suggested usages alongside Bayesian hypothesis tests.

The intention is that beginners can confidently use statistics – classical and Bayesian – on practical problems. The tests include t tests, ANOVA and their non-parametric equivalents; correlations and regression; and categorical tests, including binomial, multinomial, ‘Chi square’ test of association, and log-linear regression.

Further testing methods are discussed in outline. These include data reduction (PCA, factor analysis, and cluster analysis), logistic regression, survival analysis, and reliability. Regarded rather critically, meta-analysis, ANCOVA, and sequential regression are also included.

A chapter on reporting research, particularly in presentations, has been found very useful by students, and has therefore been replicated from previous works.