Social Science

By: David Brooks.

#1 NEW YORK TIMES BESTSELLER

With unequaled insight and brio, New York Times columnist David Brooks has long explored and explained the way we live. Now Brooks turns to the building blocks of human flourishing in a multilayered, profoundly illuminating work grounded in everyday life. This is the story of how success happens, told through the lives of one composite American couple, Harold and Erica. Drawing on a wealth of current research from numerous disciplines, Brooks takes Harold and Erica from infancy to old age, illustrating a fundamental new understanding of human nature along the way: The unconscious mind, it turns out, is not a dark, vestigial place, but a creative one, where most of the brain’s work gets done. This is the realm where character is formed and where our most important life decisions are made—the natural habitat of The Social Animal. Brooks reveals the deeply social aspect of our minds and exposes the bias in modern culture that overemphasizes rationalism, individualism, and IQ. He demolishes conventional definitions of success and looks toward a culture based on trust and humility. The Social Animal is a moving intellectual adventure, a story of achievement and a defense of progress. It is an essential book for our time—one that will have broad social impact and will change the way we see ourselves and the world.

By: Daniel Goleman.

By: CSET Exam Secrets Test Prep Team.

By: Howard S. Becker.

By: Bruce L. Berg, Howard Lune.

By: Bruce J. Malina.

By: Alan Agresti, Barbara Finlay.

The book presents an introduction to statistical methods for students majoring in social science disciplines.  No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal (lowest-level high-school algebra).

By: Arthur Aron, Elaine N. Aron, Elliot Coups.

For one-quarter/semester courses that focus on the basics in statistics or combine statistics with research methods.

The fifth edition of Statistics for the Behavioral and Social Sciences builds off an already well-established approach - emphasizing the intuitive, deemphasizing the mathematical, and explaining everything in direct, simple language - but also goes beyond these principles to further student understanding. By using definitional formulas to emphasize the concepts of statistics, rather than rote memorization, students work problems in a way that keeps them constantly aware of the underlying logic of what they are doing. 

By: Alexander L. George, Andrew Bennett.

The use of case studies to build and test theories in political science and the other social sciences has increased in recent years. Many scholars have argued that the social sciences rely too heavily on quantitative research and formal models and have attempted to develop and refine rigorous methods for using case studies. This text presents a comprehensive analysis of research methods using case studies and examines the place of case studies in social science methodology. It argues that case studies, statistical methods, and formal models are complementary rather than competitive. The book explains how to design case study research that will produce results useful to policymakers and emphasizes the importance of developing policy-relevant theories. It offers three major contributions to case study methodology: an emphasis on the importance of within-case analysis, a detailed discussion of process tracing, and development of the concept of typological theories. Case Studies and Theory Development in the Social Sciences will be particularly useful to graduate students and scholars in social science methodology and the philosophy of science, as well as to those designing new research projects, and will contribute greatly to the broader debate about scientific methods.

The Reviewer’s Guide to Quantitative Methods in the Social Sciences is designed for evaluators of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its thirty-one uniquely structured chapters cover both traditional and emerging methods of quantitative data analysis, which neither junior nor veteran reviewers can be expected to know in detail. The book updates readers on each technique’s key principles, appropriate usage, underlying assumptions, and limitations. It thereby assists reviewers to offer constructive commentary on works they evaluate, and also serves as an indispensable author’s reference for preparing sound research manuscripts and proposals.

Key features include:

The chapters cover virtually all of the popular classic and emerging quantitative techniques, thus helping reviewers to evaluate a manuscript’s methodological approach and its data analysis. In addition, the volume serves as an indispensable reference tool for those designing their own research.

For ease of use, all chapters follow the same structure:

• the opening page of each chapter defines and explains the purpose of that statistical method
• the next one or two pages provide a table listing various criteria that should be considered when evaluating and applying that methodological approach to data analysis
• the remainder of each chapter contains numbered sections corresponding to the numbered criteria listed in the opening table. Each section explains the role and importance of that particular criterion.

Chapters are written by methodological and applied scholars who are expert in the particular quantitative method being reviewed.