An Introduction to Secondary Data Analysis with IBM SPSS Statistics

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.

Table of Contents

Chapter 1. Introduction to Recommendation Engines
Chapter 2. Build Your First Recommendation Engine
Chapter 3. Recommendation Engines Explained
Chapter 4. Data Mining Techniques Used in Recommendation Engines
Chapter 5. Building Collaborative Filtering Recommendation Engines
Chapter 6. Building Personalized Recommendation Engines
Chapter 7. Building Real-Time Recommendation Engines with Spark
Chapter 8. Building Real-Time Recommendations with Neo4j
Chapter 9. Building Scalable Recommendation Engines with Mahout
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’