Description

Book Synopsis

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

Trade Review
′For a generation we have been waiting for a really good introduction to secondary data analysis. This is it.′
-- Malcolm Williams

‘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.’

-- Alasdair Rae
‘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.’ -- Roxanne Connelly
‘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.’ -- Richard Harris
′MacInnes shows newcomers the possibilities before them and teaches the safeguards needed to make the most of secondary data.’ -- Michael Hout
′Accessibly written, this is a friendly and indispensable companion for any student embarking on a secondary data analysis project. A breath of fresh air.’
-- Luke Sloan

Table of 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’

An Introduction to Secondary Data Analysis with

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    A Paperback / softback by John MacInnes

    2 in stock

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of An Introduction to Secondary Data Analysis with by John MacInnes

      Publisher: Sage Publications Ltd
      Publication Date: 19/12/2016
      ISBN13: 9781446285770, 978-1446285770
      ISBN10: 1446285774

      Description

      Book Synopsis

      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

      Trade Review
      ′For a generation we have been waiting for a really good introduction to secondary data analysis. This is it.′
      -- Malcolm Williams

      ‘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.’

      -- Alasdair Rae
      ‘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.’ -- Roxanne Connelly
      ‘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.’ -- Richard Harris
      ′MacInnes shows newcomers the possibilities before them and teaches the safeguards needed to make the most of secondary data.’ -- Michael Hout
      ′Accessibly written, this is a friendly and indispensable companion for any student embarking on a secondary data analysis project. A breath of fresh air.’
      -- Luke Sloan

      Table of 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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