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Designed to help students analyze and interpret research data using IBM SPSS, this user-friendly book, written in easy-to-understand language, shows readers how to choose the appropriate statistic based on the design, and to interpret outputs appropriately. The authors prepare readers for all of the steps in the research process: design, entering and checking data, testing assumptions, assessing reliability and validity, computing descriptive and inferential parametric and nonparametric statistics, and writing about outputs. Dialog windows and SPSS syntax, along with the output, are provided. Three realistic data sets, available on the Internet, are used to solve the chapter problems. The ne...
The authors of this unique text found that while most students can "crunch" the numbers quite easily and accurately with a calculator or computer, many have trouble seeing the "big picture" or seeing how research questions and design influence data analysis. As a result, the authors developed a semantically consistent framework that integrates traditional research approaches (experimental, quasi-experimental, comparative) into three basic kinds of research questions (difference, associational, and descriptive), which, in turn, lead to three kinds or groups of statistics with the same names. This text: *helps students become good consumers of research by demonstrating how to analyze and evalu...
Intended as a supplement for intermediate statistics courses taught in departments of psychology, education, business, and other health, behavioral, and social sciences.
This book distinguishes itself from other SPSS resources through its unique integration of the research process (including design) and the use and interpretation of the statistics. Designed to help students analyze and interpret research data, the authors demonstrate how to choose the appropriate statistic based on the research design, interpret SPSS output, and write about the output in a research paper. The authors describe the use and interpretation of these statistics in user-friendly, non-technical language. The book prepares students for all of the steps in the research process, from design and data collection, to writing about the results. The new edition features SPSS 14.0 for Window...
The Routledge Reviewer’s Guide to Mixed Methods Analysis is a groundbreaking edited book – the first devoted solely to mixed methods research analyses, or mixed analyses. Each of the 30 seminal chapters, authored by internationally renowned scholars, provides a simple and practical introduction to a method of mixed analysis. Each chapter demonstrates "how to conduct the analysis" in easy-to-understand language. Many of the chapters present new topics that have never been written before, and all chapters offer cutting-edge approaches to analysis. The book contains the following four sections: Part I Quantitative Approaches to Qualitative Data (e.g., factor analysis of text, multidimension...
Designed to help readers analyze and interpret research data using IBM SPSS, this user-friendly book shows readers how to choose the appropriate statistic based on the design; perform intermediate statistics, including multivariate statistics; interpret output; and write about the results. The book reviews research designs and how to assess the accuracy and reliability of data; how to determine whether data meet the assumptions of statistical tests; how to calculate and interpret effect sizes for intermediate statistics, including odds ratios for logistic analysis; how to compute and interpret post-hoc power; and an overview of basic statistics for those who need a review. Unique chapters on...
This book provides a showcase for "best practices" in teaching statistics and research methods in two- and four-year colleges and universities. A helpful resource for teaching introductory, intermediate, and advanced statistics and/or methods, the book features coverage of: ways to integrate these courses how to promote ethical conduct how to create writing intensive programs novel tools and activities to get students involved strategies for teaching online courses and computer applications guidance on how to create and maintain helpful web resources assessment advice to help demonstrate that students are learning tips on linking diversity to research methodology. This book appeals to veteran and novice educators and graduate students who teach research methods and/or statistics in psychology and other behavioral sciences and serves as an excellent resource in related faculty workshops. A CD with activities that readers can customize is included.
With innovative new chapters on process tracing, regression analysis, and natural experiments, the second edition of Rethinking Social Inquiry further extends the reach of this path-breaking book. The original debate with King, Keohane, and Verba_now updated_remains central to the volume, and the new material illuminates evolving discussions of essential methodological tools. Thus, process tracing is often invoked as fundamental to qualitative analysis, but is rarely applied with precision. Pitfalls of regression analysis are sometimes noted, but often are inadequately examined. And the complex assumptions and trade-offs of natural experiments are poorly understood. The second edition extends the methodological horizon through exploring these critical tools. A distinctive feature of this edition is the online placement of four chapters from the prior edition, all focused on the dialogue with King, Keohane, and Verba. Also posted online are exercises for teaching process tracing and understanding process tracing.
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This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Interactive Internet exercises that further promote undoing the misconceptions are found on the book's website. The author’s accessible discussion of each misconception has five parts: The Misconception - a brief description of the misunderstanding Evidence that the Misconception Exists – examples and claimed prevalence Why the Misconception is Dangerous – consequence of having the misunderstanding Undoing the Misconception - how...