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.
John MacInnes is Professor of Sociology at the University of Edinburgh. He has been teaching students quantitative methods and data analysis for thirty years. He has been Strategic Advisor to the UK Economic and Social Research Council on Quantitative Methods Training and currently advises the British Academy on quantitative skills, the UK Q-Step programme on statistics pedagogy and researches on statistics anxiety for the ESRC National Centre for Research Methods. He is a Fellow of the Academy of Social Sciences and the Royal Statistical Society, where he is a member of it Council. His own research and publications range over population ageing and demographic change, gender identity, national identity and the sociology of industry.
Chapter 1: Secondary Data Analysis: The Evidence is Out There Chapter 2: Understanding the Basics of Statistics Chapter 3: Doing Secondary Data Analysis in Five Minutes Chapter 4: Getting Started with SPSS Chapter 5: Dealing with Data Documentation Chapter 6: Replicating Published Analyses Chapter 7: Preparing Your Data Chapter 8: Managing and Manipulating Data Chapter 9: Introducing Linear Regression Chapter 10: Getting Started with Logistic Regression Chapter 11: Using Binary Logistic Regression Chapter 12: Practising Regression Skills With Replication Chapter 13: A Look Back: How to Enjoy `An Avalanche of Numbers'