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The ability to read published research critically is essential and is different from the skills involved in undertaking research using statistical analysis. This New Edition of Thomas R Black's best-selling text explains in clear and straightforward terms how students can evaluate research, with particular emphasis on research involving some aspect of measurement. The coverage of fundamental concepts is comprehensive and supports topics including research design, data collection and data analysis by addressing the following major issues: Are the questions and hypotheses advanced appropriate and testable? Is the research design sufficient for the hypothesis? Is the data gathered valid, reliable and objective? Are the statistical techniques used to analyze the data appropriate and do they support the conclusions reached? Each of the chapters from the New Edition has been thoroughly updated, with particular emphasis on improving and increasing the range of activities for students. As well, coverage has been broadened to include: a wider range of research designs; a section on research ethics; item analysis; the definition of standard deviation with a guide for calculation; the concept of `power' in statistical inference; calculating correlations; and a description of the difference between parametric and non-parametric tests in terms of research questions. Evaluating Social Science Research An Introduction 2nd Edition will be key reading for undergraduate and postgrduate students in research methodology and evaluation across the social sciences.
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
Recently, social science has had numerous episodes of influential research that was found invalid when placed under rigorous scrutiny. The growing sense that many published results are potentially erroneous has made those conducting social science research more determined to ensure the underlying research is sound. Transparent and Reproducible Social Science Research is the first book to summarize and synthesize new approaches to combat false positives and non-reproducible findings in social science research, document the underlying problems in research practices, and teach a new generation of students and scholars how to overcome them. Understanding that social science research has real consequences for individuals when used by professionals in public policy, health, law enforcement, and other fields, the book crystallizes new insights, practices, and methods that help ensure greater research transparency, openness, and reproducibility. Readers are guided through well-known problems and are encouraged to work through new solutions and practices to improve the openness of their research. Created with both experienced and novice researchers in mind, Transparent and Reproducible Social Science Research serves as an indispensable resource for the production of high quality social science research.
This volume offers students a basic introduction to assessing the meaning and validity of research in the social sciences and related fields. The ability to "read "published research critically is essential and is different from the skills involved in "undertaking "research using statistical analysis. Thomas R Black explains in clear and straightforward terms how students can evaluate research, with particular emphasis on research involving some aspect of measurement. The coverage of fundamental concepts is comprehensive and supports topics including research design, data collection and data analysis by addressing the following major issues: Are the questions and hypotheses advanced appropriate and testable? Is the research design sufficient for the hypothesis? Are the data gathered valid, reliable and objective? Are the statistical techniques used to analyze the data appropriate and do they support the conclusions reached?
To do research that really makes a difference -- the authors of this book argue -- social scientists need a diverse set of questions and methods, both qualitative and quantitative, in order to reflect the complexity of the world. Bringing together a consortium of voices across a variety of fields, Methods That Matter offers compelling and successful examples of mixed methods research that does just that. Discussing their own endeavors to combine quantitative and qualitative methodologies, the authors invite readers into a conversation about the best designs and practices of mixed methods to stimulate creative ideas and find new pathways of insight. The result is an engaging exploration of a promising approach to the social sciences. --
Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.
This introductory text presents basic principles of social science research through maps, graphs, and diagrams. The authors show how concept maps and mind maps can be used in quantitative, qualitative, and mixed methods research, using student-friendly examples and classroom-based activities. Integrating theory and practice, chapters show how to use these tools to plan research projects, "see" analysis strategies, and assist in the development and writing of research reports.
Provides: an historical overview of the development of the narrative approach; a guide to how narrative methods can be applied in fieldwork; how to incorporate a narrative approach within a field project; guidelines for interpreting collected or produced narratives; and useful guides for further reading.
Quantitative social science research has been expanding due to the ava- ability of computers and data over the past few decades. Yet the textbooks and supplements for researchers do not adequately highlight the revolution created by the R software [2] and graphics system. R is fast becoming the l- gua franca of quantitative research with some 2000 free specialized packages, where the latest versions can be downloaded in seconds. Many packages such as “car” [1] developed by social scientists are popular among all scientists. An early 2009 article [3] in the New York Times notes that statisticians, engineers and scientists without computer programming skills ?nd R “easy to use.” A common language R can readily promote deeper mutual respect and understanding of unique problems facing quantitative work in various social sciences. Often the solutions developed in one ?eld can be extended and used in many ?elds. This book promotes just such exchange of ideas across many social sciences. Since Springer has played a leadership role in promoting R, we are fortunate to have Springer publish this book. A Conference on Quantitative Social Science Research Using R was held in New York City at the Lincoln Center campus of Fordham University, June 18–19, 2009. This book contains selected papers presented at the conference, representing the “Proceedings” of the conference.
The A-Z is a collection of entries ranging from qualitative research techniques to statistical testing and the practicalities of using the Internet as a research tool. Alphabetically arranged in accessible, reader-friendly formats, the shortest entries are 800 words long and the longest are 3000. Most entries are approximately 1500 words in length and are supported by suggestions for further reading.