Adventures in Social Research 11/e

SAGE PUBLICATIONS INCISBN: 9781544398006

Data Analysis Using IBM SPSS Statistics

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By Earl R. Babbie, William E. Wagner, Jeanne S. Zaino
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SAGE PUBLICATIONS INC
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Format:
PAPERBACK
Pages:
536

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Description

Earl Babbie was born in Detroit, Michigan, in 1938, but his family chose to return to Vermont 3 months later, and he grew up there and in New Hampshire. In 1956, he set off for Harvard Yard, where he spent the next 4 years learning more than he initially planned. After 3 years with the US Marine Corps, mostly in Asia, he began graduate studies at the University of California-Berkeley. He received his PhD from Berkeley in 1969. He taught sociology at the University of Hawaii from 1968 through 1979, took time off from teaching and research to write full-time for 8 years, and then joined the faculty at Chapman University in Southern California in 1987. Although he is the author of several research articles and monographs, he is best known for the many textbooks he has written, which have been widely adopted in colleges throughout the United States and the world. He also has been active in the American Sociological Association for 25 years and currently serves on the ASA's executive committee. He is also past president of the Pacific Sociological Association and California Sociological Association. William E. Wagner, III, PhD, is Chair of the Department of Sociology at California State University, Dominguez Hills and Executive Director of the Social Science Research & Instructional Council of the CSU. He is co-author of Adventures in Social Research, 11th edition (SAGE, 2022), The Practice of Survey Research (SAGE, 2016), and A Guide to R for Social and Behavioral Sciences (SAGE, 2020) and author of Using IBM (R) SPSS (R) Statistics for Research Methods and Social Science Statistics, 7th edition (SAGE, 2019). Jeanne Zaino, Associate Professor of Political Science, Iona College, earned a bachelor's degree in political science and a master's degree in survey research at the University of Connecticut-Storrs. During that time, she worked as a research assistant at the Roper Center for Public Opinion Research. She went on to earn a master's degree and PhD in political science from the University of Massachusetts-Amherst. She is currently chair of the Political Science Department at Iona College in New Rochelle, New York, where she teaches courses in American government, institutions, research methods, social statistics, public opinion, scope, and methods. She and her husband, Jeff, are the proud parents of two sons, Maxim and Logan.

Part I Preparing for Data Analysis Chapter 1 Introduction: The Theory and Practice of Social Research Chapter 2 The Logic of Measurement Chapter 3 Description of Data Sets: The General Social Survey Part II Univariate Analysis Chapter 4 Using SPSS Statistics: Some Basics Chapter 5 Describing Your Data: Religiosity Chapter 6 Presenting Your Data in Graphic Form: Political Orientations Chapter 7 Recoding Your Data: Religiosity and Political Orientations Chapter 8 Creating Composite Measures: Exploring Attitudes Toward Abortion in More Depth Chapter 9 Suggestions for Further Analysis Part III Bivariate Analysis Chapter 10 Examining the Sources of Religiosity Chapter 11 Political Orientations as Cause and Effect Chapter 12 What Causes Different Attitudes Toward Abortion? Chapter 13 Measures of Association for Nominal and Ordinal Variables Chapter 14 Correlation and Regression Analysis Chapter 15 Tests of Significance Chapter 16 Suggestions for Further Bivariate Analyses Part IV Multivariate Analysis Chapter 17 Multiple Causation: Examining Religiosity in Greater Depth Chapter 18 Dissecting the Political Factor Chapter 19 A Powerful Prediction of Attitudes Toward Abortion Chapter 20 Suggestions for Further Multivariate Analyses Part V The Adventure Continues Chapter 21 Designing and Executing Your Own Survey Chapter 22 Further Opportunities for Social Research

This text has been a lifesaver! Although the material is challenging, I have been continually impressed with my student's ability to come away from this course with the ability to perform their own (small) data analysis project in the final week using what they learned. . . . Many start with zero knowledge or experience with research, and in a very short time period are able to get up to speed with the terminology, and to sift through all of the various 'rules' of data analysis (which measures of association, tests of significance, etc. to use based on their variables) like pros. -- Kristie Vise

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