Section 7.3: Further reading on Inferential Statistics

From Research Methods in Psychology

We have only had a very brief look at inferential statistics in this chapter. The area is more complex, and more controversial than you might have imagined. A good start if you would like to explore the issues further is ‘Statistics as principled argument’, by Robert Abelson (published by Erlbaum). Also, several chapters in the book ‘A Handbook for Data Analysis in the Behavioural Sciences: Methodological Issues,’ edited by Keren and Lewis, examine the basis of inferential statistics in much more depth (also published by Erlbaum). A brief look at the logic of significance testing can be found in the book ‘Understanding significance testing’, by Mohr (published by Sage). If you are feeling stronger, two books could be recommended: the first is ‘Statistical significance’ by Chow (published by Sage) is a strong defence of significance tests, against recent attacks, but you should be warned that the book is somewhat heavy going. The second book is ‘What if there were no significance tests,’ edited by Harlow, Mulaik and Steiger (published by Erlbaum). This lists arguments from both sides of the debate about the usefulness of statistical significance.