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Synopsis
The updated edition of this classic text introduces a range of techniques for exploring quantitative data including the SPSS package. Suitable for those with no previous experience of quantitative data analysis, the second edition of Exploring Data will be invaluable to students across the social sciences.
"synopsis" may belong to another edition of this title.
About the Author
Jane Elliott is Research Director, Centre for Longitudinal Studies at the Institute of Education.
From the Back Cover
The updated edition of this classic text introduces a range of techniques for exploring quantitative data. Beginning with an emphasis on descriptive statistics and graphical approaches, it moves on in later chapters to simple strategies for examining the associations between variables using inferential statistics such as chi squared. The book has been substantially revised to include the most recent approaches to data analysis, and includes step-by-step instructions on using SPSS. All these techniques are illustrated with intriguing real examples, drawn from important social research over the past three decades, designed to illuminate significant sociological and political debates.
The book shows how students can use quantitative data to answer various questions:
- Is it true that the rich are getting richer and the poor are getting poorer?
- Are crime rates really going down, and how can we tell?
- How much alcohol do men and women really drink in an average week?
- Which country in Europe has the highest average working hours?
Readers are encouraged to explore data for themselves, and are carefully guided through the opportunities and pitfalls of using statistical packages, as well as the numerous data sources readily available online.
Suitable for those with no previous experience of quantitative data analysis, the second edition of Exploring Data will be invaluable to students across the social sciences.
"About this title" may belong to another edition of this title.
- PublisherPolity Press
- Publication date2008
- ISBN 10 0745622836
- ISBN 13 9780745622835
- BindingPaperback
- LanguageEnglish
- Edition number2
- Number of pages305
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Exploring Data: An Introduction to Data Analysis for Social Scientists, 2nd Edition
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John Wiley and Sons Ltd, United Kingdom, Oxford, 2008
ISBN 10: 0745622836
ISBN 13: 9780745622835
Used
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Paperback. Condition: Very Good. The updated edition of this classic text introduces a range of techniques for exploring quantitative data. Beginning with an emphasis on descriptive statistics and graphical approaches, it moves on in later chapters to simple strategies for examining the associations between variables using inferential statistics such as chi squared. The book has been substantially revised to include the most recent approaches to data analysis, and includes step-by-step instructions on using SPSS. All these techniques are illustrated with intriguing real examples, drawn from important social research over the past three decades, designed to illuminate significant sociological and political debates. The book shows how students can use quantitative data to answer various questions: Is it true that the rich are getting richer and the poor are getting poorer? Are crime rates really going down, and how can we tell? How much alcohol do men and women really drink in an average week? Which country in Europe has the highest average working hours? Readers are encouraged to explore data for themselves, and are carefully guided through the opportunities and pitfalls of using statistical packages, as well as the numerous data sources readily available online. Suitable for those with no previous experience of quantitative data analysis, the second edition of Exploring Data will be invaluable to students across the social sciences. Download answers to exercises in book. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Seller Inventory # GOR003910430
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Exploring Data: An Introduction to Data Analysis for Social Scientists
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