Today, I submitted the manuscript for the second edition of my statistic textbook, Statistics for the Social Sciences: A General Linear Model Approach. This book has been a labor of love, and it has been a great pleasure to revisit the text and make revisions.
The first edition has been well received, with the comments I have received being overwhelmingly positive. Nevertheless, in the three years since I finished the original version, there have been some changes I wanted to make. These are things that I discovered as I used the book with my students and heard feedback from readers. The most important changes include:
- Incorporating the latest Journal Article Reporting Standards (JARS) from the American Psychological Association.
- Updates to include recommendation for statistical practice, to reflect the latest expert consensus for handling the replication crisis in the social sciences.
- Better example data sets for explaining restriction of range and ANOVA.
- A new formula guide that compiles all important formulas into one convenient location.
- More consistent mathematical notation across chapters.
- Improved discussion of statistical weights.
- Strengthening links among statistical methods in each chapter to better show how all null hypothesis tests are members of the General Linear Model.
- An added discussion of Type I error inflation when testing main effects and interactions in a multiway ANOVA.
- Fixing errors in the answer key.
- Correcting and revising some figures.
- Converting citations and references to the 7th edition of APA Style.
It was impossible to incorporate every change that people suggested to me. But I did my best to improve the book as much as possible.
The second edition is tentatively scheduled to be published at New Years’s 2021. Until then, the first edition is still available from amazon.com, Google Books, or Cambridge University Press. Although the second edition is an improvement, the first edition remains the only textbook that teaches undergraduate students the organizing principle of the General Linear Model. It is still an excellent resource for introductory statistics classes.