As part of our “Tools of the Trade” blog series, we’re highlighting resources for social science scholars and educators to aid in your research, writing, and prep work this summer. Look no further for a refresher of methods that you can use in your own work or share with your students.
How to Think Critically
Critical Thinking: Tools for Evaluating Research by Peter Nardi
This book prepares readers to thoughtfully interpret information and develop a sophisticated understanding of our increasingly complex and multi-mediated world. Peter M. Nardi’s approach helps students sharpen critical thinking skills and improve analytical reasoning, enabling them to ward off gullibility, develop insightful skepticism, and ask the right questions about material online, in the mass media, or in scholarly publications. Students will learn to understand common errors in thinking; create reliable and valid research methodologies; understand social science concepts needed to make sense of popular and academic claims; and communicate, apply, and integrate the methods learned in both research and daily life.
Stat-Spotting: A Field Guide to Identifying Dubious Data, Updated and Expanded by Joel Best
Are four million women really battered to death by their husbands or boyfriends each year? Is methamphetamine our number one drug problem today? Alarming statistics bombard our daily lives. But all too often, even the most respected publications present numbers that are miscalculated, misinterpreted, hyped, or simply misleading. This new edition contains revised benchmark statistics, updated resources, and a new section on the rhetorical uses of statistics, complete with new problems to be spotted and new examples illustrating those problems. Joel Best’s bestseller exposes questionable uses of statistics and guides the reader toward becoming a more critical, savvy consumer of news, information, and data. See also Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists, Updated Edition.
Data Mining for the Social Sciences: An Introduction by Paul Attewell and David Monaghan
We live in a world of big data: the amount of information collected on human behavior is staggering, and exponentially greater than at any time in the past. Powerful algorithms can churn through seas of data to uncover patterns. This book discusses how data mining substantially differs from conventional statistical modeling. The authors empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. This book demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.
The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies, With a New Introduction by Charles C. Ragin
The Comparative Method proposes a synthetic strategy, based on an application of Boolean algebra, that combines the strengths of both qualitative and quantitative sociology. Elegantly accessible and germane to the work of all the social sciences, and now updated with a new introduction, this book will continue to garner interest, debate, and praise.
“While not everyone will agree, all will learn from this book. The result will be to intensify the dialogue between theory and evidence in comparative research, furthering a fruitful symbiosis of ‘quantitative’ and ‘qualitative’ methods.”—Theda Skocpol, Harvard University
Time Series Analysis in the Social Sciences: The Fundamentals by Youseop Shin
This book is a practical and highly readable, focusing on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and residuals, to the evaluation and prediction of estimated models. It also explains smoothing, multiple time series analysis, and interrupted time series analysis. With a wealth of practical advice and supplemental data sets, this flexible and friendly text is suitable for all students and scholars in the social sciences.
Regression Models for Categorical, Count, and Related Variables: An Applied Approach by John P. Hoffmann
Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, and criminologists counting the number of offenses people commit are all interested in outcomes that are not continuous but must measure and analyze these events and phenomena in a discrete manner.
The book addresses logistic and probit models, including those designed for ordinal and nominal variables, regular and zero-inflated Poisson and negative binomial models, event history models, models for longitudinal data, multilevel models, and data reduction techniques.
A companion website includes downloadable versions of all the data sets used in the book.
Presenting Your Data
Principles of Data Management and Presentation by John P. Hoffmann
The world is saturated with data in words, tables, and graphics. Assuming only that students have some familiarity with basic statistics and research methods, this book provides a comprehensive set of principles for understanding and using data as part of a research, including:
• how to narrow a research topic to a specific research question
• how to access and organize data that are useful for answering a research question
• how to use software such as Stata, SPSS, and SAS to manage data
• how to present data so that they convey a clear and effective message
A companion website includes material to enhance the learning experience—specifically statistical software code and the datasets used in the examples, in text format as well as Stata, SPSS, and SAS formats.