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Contemporary societal problems are complex, intractable, and costly. Aiming to ameliorate them, social scientists formulate policies and programs, and conduct research testing the efficacy of the interventions. All too often the results are disappointing; partly because the theories guiding these studies are inappropriate, the study designs are flawed, and the empirical databases covering their research questions are sparse. This book confronts these problems of research by following this process: analyze the roots of the social problem both theoretically and empirically; formulate a study design that captures the nuances of the problem; gather appropriate empirical data operationalizing the study design; model these data using multilevel statistical methods to uncover potential causes and any biases to their implied effects; use the results by refining theory and by formulating evidence-based policy recommendations for implementation and testing.

Applying this process, the chapters focus on these social problems: political extremism; global human development; violence against religious minorities; computerization of work; reform of urban schools; and the utilization and costs of health care. Because these chapters exemplify the usefulness of multilevel modeling for the quantification of effects and causal inference, they can serve as vivid exemplars for the teaching of students. This use of examples reverses the usual procedure for introducing statistical methods. Rather than beginning with a new statistical model bearing on statistical theory and searching for illustrative data, each core chapter begins with a pressing social problem. The specific problem motivates theoretical analysis, gathering of relevant data, and application of appropriate statistical procedures. Readers can use the provided data sets and syntaxes to replicate, critique, and advance the analyses, thereby developing their ability to produce future applications of multilevel modeling.

The chapters address the multilevel data structures of these social problems by grouping observations on the micro units (level-1) by more macro-units (level-2) (e.g., school children are grouped by their classroom), and by conducting multilevel statistical modeling in contextual, longitudinal, and meta-analyses. Each core chapter applies a qualitative typology to nest the variance between the macro units, thereby crafting a "mixed-methods" approach that combines qualitative attributes with quantitative measures

This book covers research design and methodology from a unique and engaging point of view, based on accounts from influential researchers across the field of Criminology and Criminal Justice.

Most books and articles about research in criminology and criminal justice focus on how the research was carried out: the data that were used, the methods that were applied, the results that were achieved. While these are all important, they do not present a complete picture. Envisioning Criminology: Researchers on Research as a Process of Discovery aims to fill that gap by providing nuance--the “back story” of why researchers selected particular problems, how they approached those problems, and how their background, training, and experience affected the approaches they took.

As the contributions in this book demonstrate, research is not a cut-and-dried process, as all too many methods books imply, but a living, breathing–and in some ways quirky–process that is influenced by non-“scientific” factors. The path taken by a researcher is important, and an appreciation of his or her background, experience, knowledge–and the setbacks and triumphs of performing the research–provides a much more complete picture of how research is done.

The twenty-eight chapters in this book describe the back stories of their authors, which serve to enlighten readers about the interplay between the personal and the methodological. While primarily aimed as a textbook, this work will also be of interest to researchers in Criminology and Criminal Justice, and related Social and Behavioral Science fields as an account of how seminal researchers in the field developed their key contributions.

In social science research, differences among groups or changes over time are a common focus of study. While means and variances are typically the basis for statistical methods used in this research, the underlying social theory often implies properties of distributions that are not well captured by these summary measures. Examples include the current controversies regarding growing inequality in earnings, racial diferences in test scores, socio-economic correlates of birth outcomes, and the impact of smoking on survival and health. The distributional differences that animate the debates in these fields are complex. They comprise the usual mean-shifts and changes in variance, but also more subtle comparisons of changes in the upper and lower tails of distributions. Survey and census data on such attributes contain a wealth of distributional information, but traditional methods of data analysis leave much of this information untapped. In this monograph, we present methods for full comparative distributional analysis. The methods are based on the relative distribution, a nonparametric complete summary of the information required for scale--invariant comparisons between two distributions. The relative distribution provides a general integrated framework for analysis. It offers a graphical component that simplifies exploratory data analysis and display, a statistically valid basis for the development of hypothesis-driven summary measures, and the potential for decomposition that enables one to examine complex hypotheses regarding the origins of distributional changes within and between groups. The monograph is written for data analysts and those interested in measurement, and it can serve as a textbook for a course on distributional methods. The presentation is application oriented,
With a clear and engaging writing style and strong examples from the real world, this text covers current statistical techniques at an introductory level and emphasizes the clear presentation of results to a variety of audiences, making the course more useful to students and their careers. Interconnection features among chapters help students understand how all of the techniques fit together. Using varied data sets, the text features a highly rated companion website that includes videos of the author offering step-by-step explanations of how to carry out the techniques, interpret the results, and present them to varied audiences.


More inter-chapter connections have been added to improve students’ conceptual learning. Several examples (on immigration, health, and civil rights) now permeate the text for easy comparison of techniques across chapters. The section on managing data is considerably expanded to cover topics such as finding new sources of data, dealing with missing data, and how to combine data reliably. Very current examples from the scholarly literature from criminology, education, and health show how researchers use each chapter’s techniques to tell compelling stories. Instructors can choose from a variety of greatly expanded materials to enhance their lectures: engaging animations of key concepts; dynamic demonstrations of how statistics change in line with the data; short lectures on difficult-to-explain topics; and in-class exercises that will help students learn how to make sense of statistical results.
The proposed book will assemble a selection of essays that quantify the theories of Pierre Bourdieu. Our purpose is simply to provide a collection of academic pieces that demonstrate how quantitative methodological procedures are used to test the validity of existing social theory, focusing on the prominent sociologist, Pierre Bourdieu. We have chosen Bourdieu due to his international popularity in the sociology discipline, and the extensive range of his theoretical contributions.

Demonstrating the importance of quantifying, or testing, theory is frequently overlooked in university courses. Too often the sole focus is either an exploration social theory or a routine of performing quantitative methodological procedures. Students seldom receive exposure to practical applications that clearly illustrate the use of the latter to test the former. The unfortunate consequence is that students often fail to grasp the vital relationship between theory and methods, which is the basis of future sociological research.

The majority of single author sociological methods books exist in the form of undergraduate texts. Because sociologists are versed in the basics of quantitative and qualitative methodology, solo academics can reasonably author introductory texts that glean the necessary basics of both quantitative and qualitative methods. However, the same is not true of providing adequate intermediate and advanced level methodological instruction.

There is a considerable market for edited volumes of qualitative methodology. The practical benefit of such collections—both for instructors and students—is a selection of diverse topics in which researchers devote considerable attention to specific qualitative procedures. In short, an assortment of contributors can better provide intensive applications of different qualitative procedures that address unique research questions, and in a variety of settings. The end product typically incorporates a useful breadth of sociological topics, but with the requisite methodological depth (i.e. attention to procedure and depth of analysis) that is otherwise difficult for any single author to accomplish. To date, edited volumes of qualitative research are abundant, while similar quantitative compilations are rare.

Engaging and informative, this book provides students and researchers with a pragmatic, new perspective on the process of collecting survey data. By proposing a post-positivist, interviewee-centred approach, it improves the quality and impact of survey data by emphasising the interaction between interviewer and interviewee. Extending the conventional methodology with contributions from linguistics, anthropology, cognitive studies and ethnomethodology, Gobo and Mauceri analyse the answering process in structured interviews built around questionnaires.

The following key areas are explored in detail:
An historical overview of survey research The process of preparing the survey and designing data collection The methods of detecting bias and improving data quality The strategies for combining quantitative and qualitative approaches The survey within global and local contexts Incorporating the work of experts in interpersonal and intercultural relations, this book offers readers an intriguing critical perspective on survey research.

Giampietro Gobo, Ph.D., is Professor of Methodology of Social Research and Evaluation Methods at the Department of Social and Political Studies - University of Milan. He has published over fifty articles in the areas of qualitative and quantitative methods. His books include Doing Ethnography (Sage 2008) and Qualitative Research Practice (Sage 2004, co-edited with C. Seale, J.F. Gubrium and D. Silverman). He is currently engaged in projects in the area of workplace studies.

Sergio Mauceri, Ph.D., is Lecturer in Methodology of Social Sciences and teaches Quantitative and Qualitative Strategies of Social Research at the Department of Communication and Social Research - University of Rome ‘La Sapienza’. He has published several books and articles on data quality in survey research, mixed strategies, ethnic prejudice, multicultural cohabitation, delay in the transition to adulthood, worker well-being in call centres and homophobia.
Quantitative criminology has certainly come a long way since I was ?rst introduced to a largely qualitative criminology some 40 years ago, when I was recruited to lead a task force on science and technology for the President’s Commission on Law Enforcement and Administration of Justice. At that time, criminology was a very limited activity, depending almost exclusively on the Uniform Crime Reports (UCR) initiated by the FBI in 1929 for measurement of crime based on victim reports to the police and on police arrests. A ty- cal mode of analysis was simple bivariate correlation. Marvin Wolfgang and colleagues were makingan importantadvancebytrackinglongitudinaldata onarrestsin Philadelphia,an in- vation that was widely appreciated. And the ?eld was very small: I remember attending my ?rst meeting of the American Society of Criminology in about 1968 in an anteroom at New York University; there were about 25–30 people in attendance, mostly sociologists with a few lawyers thrown in. That Society today has over 3,000 members, mostly now drawn from criminology which has established its own clear identity, but augmented by a wide variety of disciplines that include statisticians, economists, demographers, and even a few engineers. This Handbook provides a remarkable testimony to the growth of that ?eld. Following the maxim that “if you can’t measure it, you can’t understand it,” we have seen the early dissatisfaction with the UCR replaced by a wide variety of new approaches to measuring crime victimization and offending.
"Prove It With Figures" displays some of the tools of the social and statistical sciences that have been applied to the proof of facts in the courtroom and to the study of questions of legal importance. It explains how researchers can extract the most valuable and reliable data that can conveniently be made available, and how these efforts sometimes go awry. In the tradition of Zeisel's "Say It with Figures," a standard in the field of social statistics since 1947, it clarifies, in non-technical language, some of the basic problems common to all efforts to discern cause-and-effect relationships. Designed as a textbook for law students who seek an appreciation of the power and limits of empirical methods, the work also is a useful reference for lawyers, policymakers, and members of the public who would like to improve their critical understanding of the statistics presented to them. The many case histories include analyses of the death penalty, jury selection, employment discrimination, mass torts, and DNA profiling. Hans Zeisel was Professor of Law and Sociology Emeritus at the University of Chicago, where he pioneered the application of social science to the law. Earlier, he had a distinguished career in public opinion and market research. He has written on a wide variety of topics, ranging from research methodology and history to law enforcement, juries, and Sheakespeare. He was elected Fellow of the American Statistical Assoication and the American Association for the Advancement of Science, and in 1980 he was inducted into the Market Research Hall of Fame. David Kaye is Regents Professor at the Arizona State University, where he teaches evidence and related topics. An author of several law textbooks and treatises, his work also has appeared in journals of
Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards. The book targets the social and health science branches such as human development, public health, sociology, psychology, education, and social work in which students bring a wide range of mathematical skills and have a wide range of methodological affinities. For these students, a successful course in statistics will not only offer statistical content but will also help them develop an appreciation for how statistical techniques might answer some of the research questions of interest to them.

This book is for use in a two-semester graduate course sequence covering basic univariate and bivariate statistics and regression models for nominal and ordinal outcomes, in addition to covering ordinary least squares regression.

Key features of the book include:

interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature

thorough integration of teaching statistical theory with teaching data processing and analysis

teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set.

This book is for a two-semester course. For a one-semester course, see

`This book is highly recommended for libraries and departments to adopt. If I had to teach a statistics class for sociology students this would be a book I would surely choose. The book achieves two very important goals: it teaches students a software package and trains them in the statistical analysis of sociological data' - Journal of Applied Statistics

This fully revised, expanded and updated Second Edition of the best-selling textbook by Jane Fielding and Nigel Gilbert provides a comprehensive yet accessible guide to quantitative data analysis. Designed to help take the fear out of the use of numbers in social research, this textbook introduces students to statistics as a powerful means of revealing patterns in human behaviour.

The textbook covers everything typically included in an introductory course on social statistics for students in the social sciences and the authors have taken the opportunity of this Second Edition to bring the data sources as current as possible. The book is full of up-to-date examples and useful and clear illustrations using the latest SPSS software.

While maintaining the student-friendly elements of the first, such as chapter summaries, exercises at the end of each chapter, and a glossary of key terms, new features to this edition include:

- Updated examples and references

SPSS coverage and screen-shots now incorporate the current version 14.0 and are used to demonstrate the latest social statistics datasets;

- Additions to content include a brand new section on developing a coding frame and an additional discussion of weighting counts as a means of analyzing published statistics;

- Enhanced design aids navigation which is further simplified by the addition of core objectives for each chapter and bullet-pointed chapter summaries;

- The updated Website at http:/ reflects changes made to the text and provides updated datasets;

A valuable and practical guide for students dealing with the large amounts of data that are typically collected in social surveys, the Second Edition of Understanding Social Statistics is an essential textbook for courses on statistics and quantitative research across the social sciences.

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