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Introduction to Secondary Data Analysis with IBM SPSS Statistics, An


Introduction to Secondary Data Analysis with IBM SPSS Statistics, An

Paperback by MacInnes, John

Introduction to Secondary Data Analysis with IBM SPSS Statistics, An

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£32.79

ISBN:
9781446285770
Publication Date:
19 Dec 2016
Language:
English
Publisher:
Sage Publications Ltd
Pages:
336 pages
Format:
Paperback
For delivery:
Estimated despatch 27 - 29 May 2024
Introduction to Secondary Data Analysis with IBM SPSS Statistics, An

Description

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.

Contents

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'

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