Behavioral Statistics Essentials

Lawrence G Herringer

• 16 december 2022
• 9781792465703

Samenvatting:

Are your psychology and social science students looking for a really detailed understanding of statistics? No? Do they want a deep dive into the theory and math behind common statistical methods? Neither do mine. The students I teach want a clear and direct explanation of when, why, and how different statistical techniques are used. Most of them see statistics as a necessary quantitative evil, but many of them can appreciate and understand behavioral statistics if they have a succinct, well-organized, and clear presentation. They want to understand the essentials.

When I started teaching statistics almost four decades ago, I used a long, thorough quantitative textbook with lots of detail. This became increasingly counterproductive. Students were often discouraged by such a book and read and learned less than from a briefer, no-frills presentation that got to the point more quickly. It was difficult to find a book that covered statistics essentials accurately and conceptually. So, I developed my own materials to accomplish this—lecture outlines, handouts, examples—and those materials eventually became this book.

If you are looking for a detailed, in-depth explanation of statistical topics and thorough discussions of related material, this is not the book for you. If you are looking for a formula-centered and mathematically oriented book that explains how to calculate every statistic, this is not the book for you either. But, if you are looking for a book with compact, easily digestible chapters, that emphasizes conceptual understanding before computation, with the essentials of when, why, and how for common behavioral statistics techniques, then this IS your book!

In a nutshell, I developed the material in this book over several decades teaching a lecture and lab course in undergraduate statistics. This material was shaped and refined by repeated feedback from students who said that it made statistics clear, understandable, and manageable for them. I have found this approach to be very successful. The book has five notable characteristics: (a) short, digestible chapters, often with a central example, that get directly to the point, (b) conceptual understanding before formulas; (c) focus on demystifying formulas and concepts; (d) practical emphasis on why a statistical method is used, when it is appropriate, and how it is applied; (e) key terms and questions to check understanding for each chapter, and a completely worked application problem for most chapters.

I tell students "I would like you to become self-sufficient by the end of the course." I want them to understand things enough to evaluate statistical information, decide what statistic is appropriate, and perform a specified statistical technique. I hope that the approach of the book facilitates this for your students as it has for mine.