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Title Details

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Title   Advanced Quantitative Data Analysis 

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Author   CRAMER D  ISBN   9780335200627  Add to shopping cart   
Publisher   Open University Press  Group   Sci/Hum. View shopping cart
Binding   Hardback Category   Sociology  Terms and conditions
Edition   1/2003 Type   Go back
Publication Year    
Subject   Social research & statistics 
Stock Status   Not currently in stock - contact store for availability 
Order Status   Not currently on order 
Synopsis There are a variety of statistical techniques used to analyse quantitative data that masters students, advanced undergraduates and researchers in the social sciences are expected to be able to understand and undertake. This book explains these techniques, when it is appropriate to use them, how to carry them out and how to write up the results. The following features characterize this book: concise and accessible introduction to calculating and interpreting advanced statistical techniques; use of a small data set of simple numbers specifically designed to illustrate the nature and manual calculation of the most important statistics in each technique; succinct illustration of writing up the results of these analyses; minimum of mathematical, statistical and technical notation; annotated bibliography and glossary of key concepts.Commonly used software is introduced, and instructions are presented for carrying out analyses and interpreting the output using the computer programs of SPSS Release 11 for Windows and a version of LISREL 8.51, which is freely available online. Designed as a textbook for postgraduate and advanced undergraduate courses across the socio-behavioural sciences, this book can also serve as a personal reference for researchers in disciplines such as sociology and psychology.
Contents:
Introduction - grouping quantitative variables together; exploratory factor analysis; confirmatory factor analysis; cluster analysis - explaining the variance of a quantitative variable; stepwise multiple regression; hierarchical multiple regression - sequencing the relationships between three or more quantitative variables; path analysis assuming no measurement error; path analysis accounting for measurement error - explaining the probability of a dichotomous variable; binary logistic regression - testing differences between group means; an introduction to analysis of variance and covariance; unrelated one-way analysis of covariance; unrelated two-way analysis of variance - discriminating between groups; discriminant analysis - analysing frequency tables with three or more qualitative variables; log-linear analysis.
READERSHIP: Undergraduate [U]; Postgraduate [P]; Research & Professional [R]

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