Data Analysis with SPSS (3rd Edition)

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9780205483877: Data Analysis with SPSS (3rd Edition)

Data Analysis with SPSS is designed to teach students how to explore data in a systematic manner using the most popular professional social statistics program on the market today.

 

Written in ten manageable chapters, this book first introduces students to the approach researchers use to frame research questions and the logic of establishing causal relations. Students are then oriented to the SPSS program and how to examine data sets. Subsequent chapters guide them through univariate analysis, bivariate analysis, graphic analysis, and multivariate analysis. Students conclude their course by learning how to write a research report and by engaging in their own research project.

 

Each book is packaged with a disk containing the GSS (General Social Survey) file and the States data files. The GSS file contains 100 variables generated from interviews with 2,900 people, concerning their behaviors and attitudes on a wide variety of issues such as abortion, religion, prejudice, sexuality, and politics. The States data allows comparison of all 50 states with 400 variables indicating issues such as unemployment, environment, criminality, population, and education. Students will ultimately use these data to conduct their own independent research project with SPSS.

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From the Back Cover:

Data Analysis with SPSS

Third Edition

 

By: Stephen A. Sweet (Cornell University)

Karen Grace-Martin

 

Basic Approach:

 

Data Analysis with SPSS is designed to teach students how to explore data in a systematic manner using the most popular professional social statistics program on the market today.

 

New to This Edition:

  • Updated for use with SPSS Version 15.
  • Most current data available on attitudes and behaviors from the 2004 General Social Surveys.
  • Graphing techniques are now integrated through the introduction of numerical summary statistics and discussions of univariate, bivariate, and multivariate methods.
  • Two new chapters on bivariate analysis techniques, such as ANOVA and T-tests, are especially useful for students in psychology or education departments.
  • Includes expanded and refined discussion of logistic regression (including probability and odds) and explanations of how statistics is valuable in understanding social behavior.
  • Uses the most recent data drawn from the 2006 State Rankings (Morgan & Quitno) and the 2004 General Social Surveys.
  • Includes discussion of constructing new variable construction and important concepts of reliability.

 

About the Author:

>Stephen Sweet is an assistant professor of sociology at Ithaca College and was formerly the associate director of the Cornell Work and Family Careers Institute. His books include Changing Contours of Work (2008), The Work and Family Handbook: Interdisciplinary Perspectives, Methods and Approaches (2005), Teaching Work and Family: Strategies, Activities, and Syllabi (2006), College and Society: An Introduction to the Sociological Imagination (2001), and Data Analysis with SPSS: A First Course in Applied Statistics (2008, 2003, 1998).

            His studies on work, family, community, and inequality appeared in a variety of publications, including Generations, Research in the Sociology of Work, Sex Roles, Family Relations, New Directions in Life Course Research, Journal of Vocational Behavior, Journal of Marriage and the Family, Innovative Higher Education, Journal of College Student Development, and Community, Work, and Family, Popular Music and Society, International Journal of Mass Emergencies and Disasters.  His articles on teaching and curriculum development have been published in Teaching Sociology, Critical Pedagogy in the Classroom, and Excellent Teaching in the Excellent University.

            In addition to his research and teaching responsibilities, Stephen Sweet currently serves as the Teaching Resources Specialist for the Sloan Work and Family Research Network, co-edits the Work-Family Encyclopedia, and manages the Sloan Early Career Scholars Program. 

 

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Stephen A. Sweet; Karen A. Grace-Martin
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