The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods
A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a "math camp" or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods.
Order the SPSS Student Version (ISBN: 978-1-4129-6883-6) of this text and your students will be able to practice SPSS (version 16.0)áon their laptops in the convenience of their dorm rooms (rather than in the computer labs) for just $25 more than the text alone.In this Fifth Edition of their best-selling Social Statistics for a Diverse Society, Chava Frankfort-Nachmias and Anna Leon-Guerrero use straightforward, conversational prose and emphasize common sense as they demonstrate the link between the practice of statistics and important social issues. Social Statistics for a Diverse Society helps students learn key sociological concepts through real research examples related to the dynamic relationship between race, class, gender, and other social variables. An emphasis on SPSS® for Windows (version 16.0) throughout the book, in conjunction with General Social Survey data, introduces one of the most commonly used analytical software packages in the field. Each chapter ends with a demonstration of a related SPSS procedure, along with a set of useful exercises to help students practice what they learn. New and Retained FeaturesNew and updated real-world examples, drawn from a wide range of sources, including news stories, government reports, scholarly research, the National Opinion Research Center General Social Survey and the Monitoring the Future Survey, help students combine an understanding of statistics with an increased understanding of social issues Significant student-friendly reorganization of the text provides descriptive and inferential statistics in discrete units first, followed by coverage of data analysis Updated statistical applications in examples now include social issues beyond race and gender, such as class and mobility Reading the Research Literature sections in most chapters help students read and interpret statistical information in professional and scholarly publications Fully revitalized learning aids, including new end-of-chapter exercises, Learning Checks, and Statistics in Practice and A Closer Look boxes A new data set available on the Study Site applies to criminology and social work research issues Ancillaries Instructor Resources on CD-Rom feature a new test bank with a wide variety of test questions, PowerPoint slides for each chapter, illustrations from the book, and teaching tips. Contact Customer Care at 1-800-818-SAGE (7243). A Student study site at www.pineforge.com/frankfort-nachmiasstudy5 contains interactive quizzes, e-flashcards, data sets, online research activities, SAGE journal articles and more. Social Statistics for a Diverse Society, Fifth Edition is appropriate for use in Introduction to Statistics, Social Statistics, Research Methods and Data Analysis courses in all of the social sciences. á
A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a "math camp" or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods.
Simply put, Thinking Through Statistics is a primer on how to maintain rigorous data standards in social science work, and one that makes a strong case for revising the way that we try to use statistics to support our theories. But don’t let that daunt you. With clever examples and witty takeaways, John Levi Martin proves himself to be a most affable tour guide through these scholarly waters. Martin argues that the task of social statistics isn't to estimate parameters, but to reject false theory. He illustrates common pitfalls that can keep researchers from doing just that using a combination of visualizations, re-analyses, and simulations. Thinking Through Statistics gives social science practitioners accessible insight into troves of wisdom that would normally have to be earned through arduous trial and error, and it does so with a lighthearted approach that ensures this field guide is anything but stodgy.
A Research Primer for the Social and Behavioral Sciences provides an introductory but comprehensive overview of the research process that primarily concerns human subjects. This book discusses the methods of acquiring knowledge, importance of a well-chosen problem, review of the literature, and relationship between theory-building and hypothesis-testing. The common sources of invalidity in practice, non-experimental research types, Stevens' classification of scales, and estimation based on probabilistic sampling are also elaborated. This text likewise covers the role of computer in research, techniques for analysis of data, univariate and bivariate statistics, and assumptions underlying analysis of variance. Other topics include the canonical correlation analysis, non-parametric analysis of variance, deterministic problem analysis techniques, and common errors in presentation of findings. This publication is intended for novice investigators in the broad category of social and behavioral sciences.
Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why one should consider diving into more detailed treatments of computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory factor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.
This accessible introduction to the theory and practice of longitudinal research takes the reader through the strengths and weaknesses of this kind of research, making clear: how to design a longitudinal study; how to collect data most effectively; how to make the best use of statistical techniques; and how to interpret results. Although the book provides a broad overview of the field, the focus is always on the practical issues arising out of longitudinal research. This book supplies the student with all that they need to get started and acts as a manual for dealing with opportunities and pitfalls. It is the ideal primer for this growing area of social research.
Sharpen your tools -- How to formulate a question -- How do you choose a site? -- Talking to people -- Hanging out -- Ethics in research -- Comparing -- Dealing with documents -- Interpreting it and writing it up