The SPSS Guide to Data Analysis is a clear, practical, systematic presentation of basic statistical techniques. This easy-to-follow book provides a comprehensive overview of the entire research process from question formulations through sampling, data collection and data analysis. In clear, descriptive language, this book explains how to design research for computer analysis, get data into the computer and perform simple analyses. Actual survey data sets are used to explain these fundamental concepts. The data sets are available on diskette, and a corresponding instructor's manual is also available.

SPSS for Windows is the most widely used computer package for analyzing quantitative data. In a clear, readable, non-technical style, this book teaches beginners how to use the program, input and manipulate data, use descriptive analyses and inferential techniques, including: " t"-tests, analysis of variance, correlation and regression, nonparametric techniques, and reliability analysis and factor analysis. The author provides an overview of statistical analysis, and then shows in a simple step-by-step method how to set up an SPSS file in order to run an analysis as well as how to graph and display data. He explains how to use SPSS for all the main statistical approaches you would expect to find in an introductory statistics course. The book is written for users of Versions 6 and 6.1, but will be equally valuable to users of later versions.

This latest edition has been fully updated to accommodate the needs of users of SPSS Releases 17, 18 and 19 while still being applicable to users of SPSS Releases 15 and 16. As with previous editions, Alan Bryman and Duncan Cramer continue to offer a comprehensive and user-friendly introduction to the widely used IBM SPSS Statistics. The simple, non-technical approach to quantitative data analysis enables the reader to quickly become familiar with SPSS and with the tests available to them. No previous experience of statistics or computing is required as this book provides a step-by-step guide to statistical techniques, including: Non-parametric tests Correlation Simple and multiple regression Analysis of variance and covariance Factor analysis. This book comes equipped with a comprehensive range of exercises for further practice, and it covers key issues such as sampling, statistical inference, conceptualization and measurement and selection of appropriate tests. The authors have also included a helpful glossary of key terms. The data sets used in Quantitative Data Analysis with IBM SPSS 17, 18 and 19 are available online at http://www.routledgetextbooks.com/textbooks/_author/bryman-9780415579193/; in addition, a set of multiple-choice questions and a chapter-by-chapter PowerPoint lecture course are available free of charge to lecturers who adopt the book.

This latest edition of this best-selling textbook has been completely updated to accommodate the needs of users of SPSS Release 10 for Windows. As with previous editions, Alan Bryman and Duncan Cramer provide a non-technical approach to quantitative data analysis and a user-friendly introduction to the widely used SPSS for Windows. They assume no previous familiarity with either statistics or computing, but take readers step-by-step through techniques, including: * Correlation * Simple and multiple regression * Multivariate analysis of variance and covariance * Factor analysis They also include a comprehensive range of exercises for further practice and cover issues such as sampling, statistical significance, conceptualisation and measurement and the selection of appropriate tests. For further information or to download the book's datasets, please visit the website: http://www.routledge.com/textbooks/titles/quant10.html

This book provides readers with two major practical insights. Firstly, on the basis of statistical inquiry it identifies the significance of socio-cultural elements that encourage user-instigated transformation. Secondly, it employs layout pattern analysis to distinguish transformation patterns, hence revealing an unbroken cultural link between residents and their roots. The book also sheds new light on the transformation of public housing in the context of culture-sensitive communities in Northern Nigeria. The research work is directed towards developing culture-responsive public housing design frameworks that are rooted in the current users’ experiences. As a result, a broad portrait of prime design emerges from said experiences. In order to accomplish this goal, the study takes into account both phenomenological and interpretive dimensions. In the process, the cultural factors behind residents’ transformations are uncovered.

This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using SPSS. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots and code from SPSS and recommends evidence-based best-practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon to help facilitate grasp of the key issues users will face while applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper-level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.

A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.