Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
---|---|---|---|---|---|
Searching... | 33000000002371 | QA276.45.S77 M33 2017 | Open Access Book | Book | Searching... |
On Order
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 booksUsing 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 Website | p. viii |
About the Author | p. ix |
Acknowledgements | p. x |
1 Secondary Data Analysis: The Evidence is Out There | p. 1 |
2 Understanding the Basics of Statistics | p. 11 |
3 Doing Secondary Data Analysis in Five Minutes | p. 41 |
4 Getting Started with SPSS | p. 67 |
5 Dealing with Data Documentation | p. 111 |
6 Replicating Published Analyses | p. 135 |
7 Preparing Your Data | p. 161 |
8 Managing and Manipulating Data | p. 193 |
9 Introducing Linear Regression | p. 211 |
10 Getting Started with Logistic Regression | p. 245 |
11 Using Binary Logistic Regression | p. 265 |
12 Practising Regression Skills with Replication | p. 301 |
13 A Look Back: How to Enjoy 'An Avalanche of Numbers' | p. 311 |
References | p. 320 |
Index | p. 321 |