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Other titles in the Quantitative Applications in the Social Sciences series:
Quantitative Applications in the Social Sciences #103: Data Analysis: An Introductionby Michael S., Professor Lewis-beck
Synopses & Reviews
This accessible introduction to data analysis focuses on the interpretation of statistical results, in particular those which come from nonexperimental social research. It will provide social science researchers with the tools necessary to select and evaluate statistical tests appropriate for their research question.
Using a consistent data-set throughout the book to illustrate the various analytic techniques, Michael Lewis-Beck covers topics such as univariate statistics, measures of association, the statistical significance of the relationship between two variables, simple regression in which the dependent variable is influenced by a single independent variable, and multiple regression.
A] valuable addition s] to the stock of material available for fledgling social scientists. Lewis-Bec's book is best for early nurture. . .
--Eric Tanenbaum in ESRC Data Archive Bulletin
This book, I predict, will turn the statistics-shy into eager practitioners, and skillful ones to boot. . . . It's a masterpiece of clarity and appliedness, written in a refreshing and engaging style. Not only is a lot of ground covered--as much as can be packed into a first-semester course in data analysis--but the author also grapples with issues of statistical theory (specification error, collinearity, least-squares estimation).
--Helmet Norpoth, SUNY at Stony Brook
This is a very fine book that will make an excellent addition to the Sage quantitative application series. It does a nice job of illustrating how data analysis is conducted by taking a simple, easy-to-motivate example and following it through the entire gamut of data analysis steps.
--Herbert Weisberg, The Ohio State University
Written at a level appropriate for the advanced undergraduate course on data analysis, this accessible volume introduces the reader to the art of data analysis from data-gathering to multiple regression in which a dependent variable is influenced by several independent variables. The book focuses on the interpretation of a statistical result, in particular those that come from nonexperimental social research. Using a consistent data set throughout the book in order to illustrate the various analytic techniques, the author covers such topics as univariate statistics, measures of association, the statistical significance of the relationship between two variables, and simple regressionwhere the dependent variable is influenced by a single independent variable. The last chapter offers analysis recommendations. Data Analysis will provide social science researchers with the tools to select and evaluate statistical tests appropriate for their particular research question.
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