Just Plain Data Analysis: Finding, Presenting, and Interpreting Social Science Data

by Gary M. Klass

Just Plain Data Analysis teaches students statistical literacy skills that they can use to evaluate and construct arguments about public affairs issues grounded in numerical evidence. The book addresses skills that are often not taught in introductory social science research methods courses and that are often covered sketchily in the research methods textbooks: where to find commonly used measures of political and social conditions; how to assess the reliability and validity of specific indicators; how to present data efficiently in charts and tables; how to avoid common misinterpretations and misrepresentations of data; and how to evaluate causal arguments based on numerical data. With a new chapter on statistical fallacies and updates throughout the text, the new edition teaches students how to find, interpret, and present commonly used social indicators in an even clearer and more practical way.

202 pages, Hardcover

First published May 21, 2008

Reviews

[Bob · Rating 4 out of 5]

Any effort to teach numerical and statistical literacy to a general audience is a good one. In chapters that present and analyze statistical argumentation, with an emphasis on the social sciences, Prof. Klass's treatment dissects the valid and invalid rhetoric that surrounds highly charged policy topics of today, from crime to healthcare reform to education to global warming, with a passing mention of "Moneyball" sabermetrics in baseball for a topical change of pace. Students assigned chapters from this book prior to classroom discussions will be immediately engaged, if perhaps triggered into preconceived notions and biases due to the politically contentious nature of the examples; Klass deserves kudos for confronting today's issues rather than retreating to safer territory. Most compelling and useful to all viewpoints is the section presenting statistical fallacies within the broader category of classical fallacies of logic. My only criticism: while students will know how to rip apart a faulty statistical presentation after absorbing the book's lessons, there is somewhat less emphasis on the original construction of proper statistical arguments.