Cover image for An Introduction to SECONDARY DATA ANALYSIS with IBM SPSS STATISTICS
Title:
An Introduction to SECONDARY DATA ANALYSIS with IBM SPSS STATISTICS
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Physical Description:
x, 324 pages : illustrations ; 25 cm
ISBN:
9781446285770

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33000000002371 QA276.45.S77 M33 2017 Open Access Book Book
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Summary

Summary

Many professional, high-quality surveys collect data on people′s behaviour, experiences, lifestyles and attitudes. The data they produce is more accessible than ever before. This book provides students with a comprehensive introduction to using this data, as well as transactional data and big data sources, in their own research projects. Here you will find all you need to know about locating, accessing, preparing and analysing secondary data, along with step-by-step instructions for using IBM SPSS Statistics.

You will learn how to:

Create a robust research question and design that suits secondary analysis Locate, access and explore data online Understand data documentation Check and ′clean′ secondary data Manage and analyse your data to produce meaningful results Replicate analyses of data in published articles and books

Using case studies and video animations to illustrate each step of your research, this book provides you with the quantitative analysis skills you′ll need to pass your course, complete your research project and compete in the job market. Exercises throughout the book and on the book′s companion website give you an opportunity to practice, check your understanding and work hands on with real data as you′re learning.


Author Notes

John MacInnes is Professor of Sociology and Associate Dean (Quantitative Methods) at the University of Edinburgh, and Strategic Advisor on Quantitative Skills to the British Academy.


Table of Contents

Companion Websitep. viii
About the Authorp. ix
Acknowledgementsp. x
1 Secondary Data Analysis: The Evidence is Out Therep. 1
2 Understanding the Basics of Statisticsp. 11
3 Doing Secondary Data Analysis in Five Minutesp. 41
4 Getting Started with SPSSp. 67
5 Dealing with Data Documentationp. 111
6 Replicating Published Analysesp. 135
7 Preparing Your Datap. 161
8 Managing and Manipulating Datap. 193
9 Introducing Linear Regressionp. 211
10 Getting Started with Logistic Regressionp. 245
11 Using Binary Logistic Regressionp. 265
12 Practising Regression Skills with Replicationp. 301
13 A Look Back: How to Enjoy 'An Avalanche of Numbers'p. 311
Referencesp. 320
Indexp. 321