Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.

This book integrates social science research methods and the descriptions of over 40 univariate, bivariate, and multivariate tests to include a description of the purpose, key assumptions and requirements, example research question and null hypothesis, SPSS procedures, display and interpretation of SPSS output, and what to report for each test. It is classroom tested and current with IBM SPSS 22. This expanded second edition also features companion website materials including copies of the IBM SPSS datasets used to create the SPSS output presented in the book, and Microsoft PowerPoint presentations that display step-by-step instructions on how to run popular SPSS procedures. Included throughout the book are various sidebars highlighting key points, images and SPSS screenshots to assist understanding the material presented, self-test reviews at the end of each chapter, a decision tree to facilitate identification of the proper statistical test, examples of SPSS output with accompanying analysis and interpretations, links to relevant web sites, and a comprehensive glossary. Underpinning all these features is a concise, easy to understand explanation of the material.

This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.

Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.

Using Statistical Methods in Social Science Research, Third Edition is the user-friendly text every student needs for analyzing and making sense of quantitative data. With over 20 years of experience teaching statistics, Soleman H. Abu-Bader provides an accessible, step-by-step description of the process needed to organize data, choose a test or statistical technique, analyze, interpret, and report research findings. The book begins with an overview of research and statistical terms, followed by an explanation of basic descriptive statistics. It then focuses on the purpose, rationale, and assumptions made by each test, such as Pearson's correlation, student's t-tests, analysis of variances, and simple linear regression, among others. The book also provides a wealth of research examples that clearly display the applicability and function of these tests in real-world practice. In a separate appendix, the author provides a step-by-step process for calculating each test for those who still like to understand the mathematical formulas behind these processes.

This volume is the first to provide a systematic introduction to the methods of social science for the legal professions and decision-makers in public policy fields. Designed as both a text and a convenient reference, the book provides an understanding of all the elements in the research process and acquaints the reader with the choices that are available in designing and conducting research. A particularly useful feature is each chapter's examination of research cited in specific court or public policy decisions, together with discussion of possible legal applications of various research approaches.

For the social sciences, the approach and processes in research are quite different. The type of evidence that social scientists can collect is often very dependent on the method that has been used to gather the data. The type of findings that can be discussed are often not straightforward at all, and no easy comparison can be made with the natural sciences, although this is not impossible. The methodology in the social sciences has the same role as technology and lab techniques in the natural sciences as these need to be developed rapidly to account for the increasing complexity of the natural objects to be studied. The methodologies in the social sciences need to go through an intense period of critique, reflection, and reformulation to consider the complexity of social issues under investigation. Therefore, the area of social sciences research and methodologies should continually be studied to advance the field. Approaches and Processes of Social Science Research presents new research methodologies in the social science field and aims at providing a broad introduction to the methodology of social research in its main theoretical foundations as well as in its practical applications. Readers will develop a critical thinking attitude about social problems which in turn will sharpen their analytic approach to research. This book includes four main parts: philosophical perspectives, strategies for conducting research, common approaches for handling and collecting data, and critical aspects of research writing throughout the process. While highlighting topics such as critical theory in research, ethical issues, research processes, data analysis, and more, this book is ideal for researchers in the social sciences and practitioners, stakeholders, academicians, and students interested in deepening their understanding of the ideas and the practices of social science research.

A stimulating book for social scientists considering the issues involved when deciding upon their research design.