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Data Analysis: An Introduction (Quantitative Applications in the Social Sciences)
 
 
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Data Analysis: An Introduction (Quantitative Applications in the Social Sciences) (Paperback)

by Michael S. Lewis-Beck (Author) "Social science research begins with a questions about human behavior..." (more)
Key Phrases: Student Motivation, Wintergreen College, Religious Affiliation (more...)
4.0 out of 5 stars See all reviews (1 customer review)

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Data Analysis: An Introduction (Quantitative Applications in the Social Sciences) + Applied Regression: An Introduction (Quantitative Applications in the Social Sciences) + Understanding Regression Analysis: An Introductory Guide (Quantitative Applications in the Social Sciences)
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Editorial Reviews

Product Description

"[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 regression where 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.


Product Details

  • Paperback: 88 pages
  • Publisher: Sage Publications, Inc; 1 edition (January 17, 1995)
  • Language: English
  • ISBN-10: 0803957726
  • ISBN-13: 978-0803957725
  • Product Dimensions: 8.3 x 5.3 x 0.2 inches
  • Shipping Weight: 3.2 ounces (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars See all reviews (1 customer review)
  • Amazon.com Sales Rank: #234,275 in Books (See Bestsellers in Books)

Inside This Book (learn more)
First Sentence:
Social science research begins with a questions about human behavior. Read the first page
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Student Motivation, Wintergreen College, Religious Affiliation, Library Book Return
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8 of 8 people found the following review helpful:
4.0 out of 5 stars Quick & Easy Guide to Statistics, February 1, 2001
By Carol F. Black (W.Lafayette, IN USA) - See all my reviews
As a Phd student in sociology, I find this booklet indispensable as a quick and easy reference guide to all the basics of social science statistical analysis. After going through more complicated texts such as Lewis-Beck's "Applied Regression: an Introduction" and Berry and Feldman's "Multiple Regression in Practice", I find this small booklet extremely helpful and clear in its explanations of the logic of basic bivariate and multiple regression analysis, as well as significance testing. It is quite useful as a tool to review the basic methods of analysis, and I especially like the list of regression assumptions at the end, all of which we had to memorize and explain for qualifying exams! I would only request a separate section and more detailed explanation of the Chi-square test, complete with application examples.
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