`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:/www.soc.surrey.ac.uk/uss/index.html 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.
Jane Fielding gained her DPhil in Biochemistry in 1976 to be followed by postdoctoral fellowships at Queen Elizabeth College and Imperial College, University of London. She joined Surrey University in 1981 as a researcher on several part-time contracts in the departments of Sociology, Psychology and Human Biology. In 1984 she was appointed as the Departmental Research Fellow and has been involved with the teaching of computing and quantitative methods since that time. In 1994 she took up her current lectureship in quantitative methods and was promoted to Senior Lecturer in 2001. Nigel Gilbert read for a first degree in Engineering, intending to go into the computer industry. However, he was lured into sociology and obtained his doctorate on the sociology of scientific knowledge from the University of Cambridge, under the supervision of Michael Mulkay. His research and teaching interests have reflected his continuing interest in both sociology and computer science (and engineering more widely). His main research interests are processual theories of social phenomena, the development of computational sociology and the methodology of computer simulation, especially agent-based modelling. He is Director of the Centre for Research in Social Simulation. He is also Director of the University's Institute of Advanced Studies and responsible for its development as a leading centre for intellectual interchange. He is the author or editor of several textbooks on sociological methods of research and statistics and editor of the Journal of Artificial Societies and Social Simulation.
Numbers, Data and Analysis Using Computers in Statistics Univariate Statistics Graphics for Display Measures of Central Tendency and Dispersion Graphics for Analysis The Normal Curve Correlation and Regression Bivariate Analysis Categorical Data Tables Sampling and Inference Testing Hypotheses Modelling Data