How to make the numbers shine
relatively recent advent of data journalism and visualisation, the practice of analysing data is an old one. In 1786 William Playfair, a Scottish engineer and secret agent, invented the first bar chart.was founded in 1843 and printed its first one five years later. Around the same time, as cholera plagued London, a doctor called John Snow mapped cases of the deadly disease to find the common cause among his patients. He pinpointed a local water pump and therefore had its handle removed.
Science and medicine furnish the best early examples of data analysis and visualisation. In the 1850s Florence Nightingale, who established the principles of modern nursing, used a chart to show causes of death in the Crimean war. She deployed her data to make a case for better sanitary standards in general. In America, W.E.B. du Bois, a civil-rights activist and scholar, was a pioneer of data communication.
In “The Art of Statistics” Sir David Spiegelhalter, a British statistician, demonstrates how looking at data can help to solve common problems. From hospital mortality rates to ovarian cancer screenings, many of his examples are drawn from the medical field. He also shows how other sciences, such as archaeology and engineering, have been changed by the use of statistics. A witty writer, he helps readers improve their data literacy and see the bigger picture when looking at numbers.
The infographics created by W.E.B. Du Bois and his team at the University of Atlanta at the turn of the 20th century were nothing short of visionary. Du Bois’s data visualisation still serves as an example of the power and beauty of a well-thought out chart. All of his revolutionary data designs are published together in this book. Originally his works were destined for Europe and so are described in English and French.
Separating reliable from dodgy data can be tricky. Carl Bergstrom and Jevin West, both scholars at the University of Washington, teach students how to do so. “Calling Bullshit” is their guide to navigating a world full of doubtful claims based on spurious data.
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