Statistics Explained: A Guide for Social Science Students, 2nd Edition

I have at least six different statistics texts, each with a "sure fire" way to make statistics clear. This was the only text that made that happen. The logical approach the author takes includes the derivation of formula from one-step to another. Z-scores, an easy to understand concept -- once explained -- was the first step in the evolution to the t-tests and beyond. I have this book as a hardcopy and a Kindle text, the latter for review, the former for more elaborate notes.

A reasonably sized book that delivers thoughtful explanations, as promised in the title. On average, each chapter is 15-page long, therefore it can be read while enjoying a cup of tea. And then you can go to bed satisfied that you actually finished a chapter today, and finally understood why they call it the power of a test. ANOVA seems to form the core of this book, in its various guises and usages. But my favorite chapter is the last one, which introduces the general linear model as an umbrella for most statistical concepts presented in the book. This has been a fresh take on the whole subject for me when I first read it. I take away one star because the book has no exercises for the readers to sharpen their pencils. The chapters contain some worked examples, but these are not enough for students. So you would need another book for that purpose. Also, this book is very light on probability topics.

Professor Hinton's book provides the reader with the best and clearest explanations for potentially difficult subjects such as Types I and II errors, the meaning of the sums of squares in ANOVA, and the interpretation of Pearson's R in regression. Those are topics that many beginners find hard to grasp. If you have learned "how to do" Statistics but are not sure you understand the underlying concepts this book is for you. If you need a theoretically sound review of basic Statistical concepts, at the same time as readable as possible, this book is for you too. Professor Hinton has an incredible way of explaining hard topics in crystal-clear, easily understandable detail. He does not take anything for granted. Even those afraid of Statistics may find pleasure in reading Hinton's book - the pleasure that comes from thoroughly understanding a concept. This is the second edition of a great book. Interestingly enough, if you go to Professor Hinton's Oxford Brookes University website you will see that he is not listed as a Statistics Professor. According to the website he is responsible for managing the Institute's portfolio of undergraduate modular programmes in Communication, Media and Culture; Early Childhood Studies, Education and Human Development; English Language and Linguistics; Performing Arts; Philosophy; Religion, Culture and Ethics; Sports and Coaching. Not the typical Statistics author. Certainly not the typical Statistics book. Highly recommended.

The only topics missing from this book that I wish had been discussed are validity (concurrent, longitudinal predictive, diagnostic) and item analysis (difficulty and discrimination indexes). A few pages are devoted to reliability, but I would have liked to see more detailed discussion devoted to the differences between the types of reliability measurement (test-retest, split halves, and parallel forms reliability). These minor points aside, this book is a wonderfully readable and not at all intimidating introduction to statistics. Highly recommended!

This lovely book provides a consistently straightforward and easily accessible explanation of statistics. The book takes the reader through basic concepts in a de-mystifying way, providing the intuition that got lost in the mathematics when I took statistics in college. The book strikes an excellent balance between substance and simplicity in going through the basic ideas and the math behind them, providing a role model for first explanations of substantive topics. It's nice to read a book that sticks to its task of helping the reader understand a subject broadly and thoroughly without the author seeming to be trying to impress the reader with how much he or she knows.