Agresti and Finley present statistical methods in a style that emphasizes their concepts and their application to the social sciences rather than the mathematics and computational details behind them.
Statistical Methods for the Social Sciences, 4e presents an introduction to statistical methods for students majoring in social science disciplines. No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal (lowest-level high-school algebra).
This text may be used in a one or two course sequence. Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course.
Agresti, Alan/ Finlay, Barbara
Most Helpful Customer Reviews
Your typical undergraduate student who is not a fan of mathematics education will find this book intimidating. But that's not really saying much. A student who's not math-phobic will enjoy it. It's not one of those statistics texts that tries to give just the concepts and not the underlying math. This one goes for the math -- which is the foundation of the concepts. (Conceptual explanations in plain English are here too! The book is not pure math. Anyway, statistics is equal parts numbers and reasoning.) The illustrations and diagrams are generally excellent. Each chapter ends with a large selection of questions and exercises (answers to some of these are provided at the back of the book) and a bibliography for further reading. Yes, really useful further reading -- not just academic texts, but popular science magazine articles, biographies of mathematicians, etc. Notation and terms are boxed off within the text, to be clearly noticeable upon review of...
I was subjected to an earlier edition when I took statistics as an undergraduate, and I've used the 2nd and 3rd editions as a lecturer and professor, and I believe there is no preferable alternative. Agresti and Finlay are, above all, clear and accurate. Over the last decade, I've looked at several dozen alternatives, hoping to find one that's strong in the areas where this text is weak. I've been enticed by different layouts, writing styles, even overall motifs, but am always reminded of why I (and others) have relied on this text for so long. Some alternatives are just sloppy - poor editing, excessive typographic errors, incorrect answers in the answer keys. Some others border on incompetent, confusing basic issues and not clarifying the disputes on border issues. And some, while achieving rapport through comics, comedy, or simply light humor, lose some of the subtle finesse that statistics entails. Now, this one ain't perfect. The subtleties and disputes are...
As a doctoral student with an interest in quantitative research and evaluation methodologies, I am currently using this book for a course in regression analyses. It is a fairly easy read for those who are familiar with statistics and I would recommend it to those wanting to learn more about quantitative analyses. The examples are up-to-date compared to previous editions. There appear to be no substatial content differences between this edition and the previous editions (in my experience having read both).
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