Fundamental Statistics for the Behavioral Sciences

by David C. Howell

David Howell's practical approach focuses on the context of statistics in behavioral research, with an emphasis on looking before leaping; investigating the data before jumping into a test. This provides you with an understanding of the logic behind the statistics: why and how certain methods are used rather than just doing techniques by rote. Learn faster and understand more because Howell's texts moves you beyond number crunching, allowing you to discover the meaning of statistical results and how they relate to the research questions being asked.

Genres: Psychology, Textbooks, Nonfiction, Reference, Mathematics

608 pages, Hardcover

First published January 1, 1989

Reviews

[Fed · Rating 3 out of 5]

The theory is great and the concepts are explained well. However, some of the examples are borderline inappropriate.

[Y · Rating 4 out of 5]

The author reasons through statistical concepts as though he is sharing his uninterrupted thoughts. You may personally like or hate this style. I personally liked it because I found it easy to follow along with his linear thinking. The author simplifies statistical concepts for behavioral science students very well. He also makes use of very interesting examples (real studies) from the behavioral sciences to keep the reader engaged and mindful of how the learned methodologies apply to data, knowledge, and research in the field. Above all, I love how he includes data from real studies for us to perform our analyses in practice.

There are some shortcomings to the book. The book lacks in mathematical elaborations and explanations of formulas, but that is to be expected since this textbook is not aimed at a mathematical audience but at behavioral science students. Those students would likely not welcome additional mathematical derivations or explanations that are unnecessary for their practical training purposes. Moreover, although the book typically alludes to good quality studies, the author infrequently references studies with questionable methodologies, confounding variables, and hypotheses (e.g. pg. 404). Moreover, it is a little annoying how he frequently references studies discussed in prior chapters, causing students to have to skim back and locate the data to perform their calculations. Moreover, his writing can be at times ambiguous and explanations unnecessarily complicated. Overall, however, the author does a good job at making statistics understandable to a scientific audience without a mathematical background.

[Jennifer · Rating 3 out of 5]

Still speedreading my way through this for a class.

This book is written in a style more like one long conversation/narrative (or lecture) by with author with the reader rather than your typical, bullet-pointed, simplified textbook. There are pros and cons to this- you get a really thorough understanding of the background/context of things, and it CAN be a rather interesting read if you can spare large chunks of your time to engage in and enjoy the discussion (the author has clearly put a lot of thought into his examples and used his teaching experience in explaining things as if TO a student). On the other hand, if you were expecting the key formulas and points to be highlighted, set in bold, bulletpointed for you... you will need to take notes as you read. Even the summaries read like a end-of-lecture recap ('we covered...') instead of repeating key information.

I've also found 3 typos/minor errors so far (and counting). Not major issues, but in a stats textbook, small inaccuracies can add a lot to the confusion. May check out author's website later to see if it's been noted?

There are also links to loads of websites for you to explore, but at least one (Dartmouth ones) appeared to have been moved or taken down. For the THOROUGH, but lazy... the screenshots and summaries in the textbook are nice.