Adventures in Social Research: Data Analysis Using IBM SPSS Statistics
SAGE Publications Inc
‘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.’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:
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.