EBOOK: ADVANCED QUANTITATIVE DATA ANALYSIS (e-bok)
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E-bok
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Språk
Engelska
Antal sidor
208
Utgivningsdatum
2003-07-16
Förlag
McGraw-Hill Education
Antal komponenter
1
ISBN
9780335224661
EBOOK: ADVANCED QUANTITATIVE DATA ANALYSIS (e-bok)

EBOOK: ADVANCED QUANTITATIVE DATA ANALYSIS E-bok

E-bok (PDF - DRM), Engelska, 2003-07-16
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*What do advanced statistical techniques do?*When is it appropriate to use them?*How are they carried out and reported?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. Most books which describe these techniques do so at too advanced or technical a level to be readily understood by many students who need to use them. In contrast the following features characterise 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 conceptsCommonly 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 will also serve as a personal reference for researchers in disciplines such as sociology and psychology.
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Fler böcker av Duncan Cramer

Innehållsförteckning

Series editors foreword

Preface

1 Introduction


part 1

Grouping quantitative variables together


2 Exploratory factor analysis

3 Confirmatory factor analysis

4 Cluster analysis


part 2

Explaining the variance of a quantitative variable



5 Stepwise multiple regression

6 Hierarchical multiple regression


part 3

Sequencing the relationships between three or more quantitative
variables



7 Path analysis assuming no measurement error

8 Path analysis accounting for measurement error



PART 4

Explaining the probability of a dichotomous variable



9 Binary logistic regression



PART 5

Testing differences between group means



10 An introduction to analysis of variance and covariance

11 Unrelated one-way analysis of covariance

12 Unrelated two-way analysis of variance


part 6

Discriminating between groups


13 Discriminant analysis


part 7

Analysing frequency tables with three or more qualitative variables

14 Log-linear analysis

Glossary

References

Index