Pub. Date:
SAGE Publications
Making Sense of Data in the Media / Edition 1

Making Sense of Data in the Media / Edition 1

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"There are two ways to learn about statistics. You could endure pages of maths and formulae, or you could learn from informative case studies exploring how, when and why data is used well or badly in today's society. I prefer the second option. Happily, the authors do too." - Richard Harris, University of Bristol

This is not your typical statistics textbook.

The amount of data produced by and presented in the media has never been greater. But can we trust what we are being shown? In an age of fake news, how can you understand what data is real, misleading, or simply plain wrong?

This book shows you how to critically evaluate the data you see in the media. It weaves everyday real-life examples with statistical concepts in a way that makes statistics come alive. No complex equations, no overly technical language.

This isn’t just learning the techniques needed to pass a stats course. This is a book for anyone who reads (or writes) the news, watches adverts, or goes on the Internet. It will give you tools and knowledge you can apply every day to make sense of the use, and misuse, of data in the media.

Product Details

ISBN-13: 9781526447203
Publisher: SAGE Publications
Publication date: 12/20/2019
Pages: 272
Product dimensions: 6.69(w) x 9.53(h) x (d)

About the Author

Andrew Bell is a Lecturer at the Sheffield Methods Institute, University of Sheffield. His research spans a wide range of social sciences and beyond, with work on social inequalities, segregation, mental health, education and more. He also investigates the performance of different quantitative methods for use in the social sciences, with a focus on multilevel models. His twitter is @andrewjdbell.

Todd Hartman is Senior Lecturer in Quantitative Social Sciences at the Sheffield Methods Institute. His research focuses on political psychology, especially political attitudes and inter-group relations. He has extensive experience conducting surveys and experiments. His twitter is @tkhartman

Aneta Piekut is a Lecturer at the Sheffield Methods Institute, the University of Sheffield. Her research focuses on the relationship between ethnic diversity and social cohesion, attitudes towards immigration and ethnic minorities, as well as integration and socio-spatial segregation. She teaches undergraduate students how to design a survey, do a mixed-methods research and how to replicate a scientific paper. Her twitter is @anetapiekut

Alasdair Rae is the founder of Automatic Knowledge Ltd, a UK-based data and insights company, focusing on spatial data analysis and the built environment. Prior to that, he was a Professor of Urban Studies and Planning at the University of Sheffield. He is a Fellow of the Royal Scottish Geographical Society, a recipient of the Royal Town Planning Institute's Sir Peter Hall award for Wider Engagement, a former Commissioner of the UK2070 Commission, and a winner of the Royal Statistical Society’s ‘Stat of the Year’. His most recent academic work has focused on spatial analysis, deprivation, housing markets and megaregions, and his work frequently appears in the national and international media. He has a Ph D from the University of Liverpool, an MA from The Ohio State University and a BA from the University of Strathclyde.

Mark Taylor is Senior Lecturer in Quantitative Methods (Sociology) at the Sheffield Methods Institute, University of Sheffield, and is AHRC Leadership Fellow (Creative Economy) until 2021. His research interests are in the sociology of culture: in consumption, production, and education, and its relationship to inequality. He spends a lot of time visualising data, and wrangling data into a shape where it can be visualised. His twitter is @markrt

Table of Contents

Chapter 1 Introduction
Chapter 2 How to make numbers sound big, or small, even when they aren’t: “Is that a lot?”
Chapter 3 Recognizing which numbers you should trust: “Where is the data from?”
Chapter 4 Making surveys representative: “Who you gonna call?”
Chapter 5 Graphics in the media and how to read them: “What does this mean?
Chapter 6 Maps in the media: “Where is this happening? "
Chapter 7 Mapping patterns and people: why does geography matter?
Chapter 8 Understanding uncertainty in estimation: “are you sure?”
Chapter 9 Ranking with league tables: “What's the best? "
Chapter 10 When a relationship (doesn’t) mean causality: “How did that happen? "
Chapter 11 Surprising quirks in the media: “Is that possible? "
Chapter 12 Conclusion

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