Understanding Significance Testing (Quantitative Applications in the Social Sciences)

"The book begins with a clear and readable explanation of the idea of the sampling distribution....This text should be useful to the nonstatistical social researcher who wants to understand the concept of significance testing."

--Social Research Association News

"Good for refreshing a few basic ideas."

--Journal of the American Statistical Association

Significance testing is the most used, and arguably the most useful, of all techniques for analyzing social science data. In this practical volume, Mohr first defines basic terms such as variance, standard deviation, and parameter. He then carefully outlines the uses of significance testing and examines sampling distributions, probability distributions, and normal and t-tests of significance. Readers at all levels of research experience, from the first-semester student to the seasoned practitioner, will profit from this handy volume.

Professor Mohr is currently working on a theoretical paper in program evaluation called An Exploration in the Theory of Valuing and a research monograph called The Impacts of Sponsored Research Dollars on Academic Institutions. The next project will be an edited volume with critique called The Case Study As a Research Design in Social Science.