Making Sense of Statistical Methods in Social Research is a critical introduction to the use of statistical methods in social research. It provides a unique approach to statistics that concentrates on helping social researchers think about the conceptual basis for the statistical methods they're using. Whereas other statistical methods books instruct students in how to get through the statistics-based elements of their chosen course with as little mathematical knowledge as possible, this book aims to improve students' statistical literacy, with the ultimate goal of turning them into competent researchers. Making Sense of Statistical Methods in Social Research contains careful discussion of the conceptual foundation of statistical methods, specifying what questions they can, or cannot, answer. The logic of each statistical method or procedure is explained, drawing on the historical development of the method, existing publications that apply the method, and methodological discussions. Statistical techniques and procedures are presented not for the purpose of showing how to produce statistics with certain software packages, but as a way of illuminating the underlying logic behind the symbols. The limited statistical knowledge that students gain from straight forward 'how-to' books makes it very hard for students to move beyond introductory statistics courses to postgraduate study and research. This book should help to bridge this gap.
Making Sense of Statistical Methods in Social Research is a critical introduction to the use of statistical methods in social research. It provides a unique approach to statistics that concentrates on helping social researchers think about the conceptual basis for the statistical methods they're using. Whereas other statistical methods books instruct students in how to get through the statistics-based elements of their chosen course with as little mathematical knowledge as possible, this book aims to improve students' statistical literacy, with the ultimate goal of turning them into competent researchers. Making Sense of Statistical Methods in Social Research contains careful discussion of the conceptual foundation of statistical methods, specifying what questions they can, or cannot, answer. The logic of each statistical method or procedure is explained, drawing on the historical development of the method, existing publications that apply the method, and methodological discussions. Statistical techniques and procedures are presented not for the purpose of showing how to produce statistics with certain software packages, but as a way of illuminating the underlying logic behind the symbols. The limited statistical knowledge that students gain from straight forward 'how-to' books makes it very hard for students to move beyond introductory statistics courses to postgraduate study and research. This book should help to bridge this gap.
These four volumes provide a collection of key publications on categorical data analysis, carefully put together so that the reader can easily navigate, understand and put in context the major concepts and methods of analysing categorical data. The major work opens with a series of papers that address general issues in CDA, and progresses with publications which follow a logical movement from the statistics for analysing a single categorical variable, to those for studying the relationships between two and more categorical variables, and to categorical variables in some of more advanced methods, such as latent class analysis. Edited and introduced by a leading voice in the field, this collection helpfully includes both theoretical and applied items on its theme, in order to help the reader understand the methods and use them in empirical research. Volume 1: Basic Concepts and Principles Volume 2: Statistical Methods for Analysing Associations Volume 3: Log-Linear and Logistic Regression Models Volume 4: Advanced and Graphical Statistical Methods
How can we analyse the intersectional effects of multiple factors on experiences of disenfranchisement? This book equips you with the methodological tools to uncover new insights. First providing a critical examination of long-standing methodologies in intersectionality research, it then shines a spotlight on analytical techniques such as qualitative comparative analysis, multilevel models, mediation and moderation, and mixed methods designs. With chapter objectives, real-world research examples, further reading and reflective questions, it will equip you with the methodological tools to understand intersectionality in specific social settings. The book: * Bridges the gap between intersectionality as a theory and an empirical research practice. * Extends existing approaches to analysing intersectionality in a traditionally qualitative field. * Inspires creativity and celebrates a variety of effective methods for studying intersectionality. Innovative and thought-provoking, this book is ideal for any student or researcher looking to harness the power of empirical evidence to explore inequality and injustice.
How can we analyse the intersectional effects of multiple factors on experiences of disenfranchisement? This book equips you with the methodological tools to uncover new insights. First providing a critical examination of long-standing methodologies in intersectionality research, it then shines a spotlight on analytical techniques such as qualitative comparative analysis, multilevel models, mediation and moderation, and mixed methods designs. With chapter objectives, real-world research examples, further reading and reflective questions, it will equip you with the methodological tools to understand intersectionality in specific social settings. The book: * Bridges the gap between intersectionality as a theory and an empirical research practice. * Extends existing approaches to analysing intersectionality in a traditionally qualitative field. * Inspires creativity and celebrates a variety of effective methods for studying intersectionality. Innovative and thought-provoking, this book is ideal for any student or researcher looking to harness the power of empirical evidence to explore inequality and injustice.
