An Introduction to Secondary Data Analysis with IBM SPSS Statistics
- John MacInnes - University of Edinburgh, UK
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.
Supplements
'For a generation we have been waiting for a really good introduction to secondary data analysis. This is it.'
‘A concise, compelling and engaging new text, this is a valuable addition to the bookshelves of anyone wanting to really get to grips with secondary data analysis.’
‘An excellent text that engages with the real-world practice of analysing existing quantitative data resources. The book covers the neglected issues of data documentation, data management, and replication that are central to effective research.’
‘There are lots of books about statistics. But there are very few that tell students what they really need to know: how to acquire and manage data, and how to use them to answer questions relevant to their studies. This book fills the gap in a clearly written and user-friendly way, and is full of interesting and practical examples. It should be core reading.’
'MacInnes shows newcomers the possibilities before them and teaches the safeguards needed to make the most of secondary data.’
'Accessibly written, this is a friendly and indispensable companion for any student embarking on a secondary data analysis project. A breath of fresh air.’
Still not sure how to implement it exactly, as there are other great books on statistics out there, especially the "classics" from Andy Field. But - good read with some nice hints as well!
John MacInnes is a secondary analyst with impecable credentials in the teaching of quantitative methods, so I had high hopes for this book. I'm delighted to report that my expectations were exceeded, within half an hour of picking it up I was ordering copies for the library and mentally updating a module reading list.
This is the first text book on the topic for ten years on the topic, and it is more extensive than predecessors. It is both practical and engaging and I believe students will enjoy it. It's structure constitutes a course in data analysis using secondary data which gets as far as logistic regression. The first four chapters cover the basics of secondary analysis introducing the method, SPSS and statistics, with a chapter that exposes readers to the general approach. The middle four chapters are the least travelled ground covering the core secondary analysis skills of data documentation and data manipulation. Chapters 9 - 12 cover modelling, while the final chapter summarises some key topics.
This book is well worth a look if you are teaching surveys or any statistics course using SPSS. If you are teaching surveys the book will provide a very good sense of how to use data. If you are teaching with SPSS at all the book is a useful reference for the stuff that tends to get lost down the cracks between modules; recoding, file restructuring, syntax and documentation. If you are teaching secondary analysis this is your previously missing core text.
