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  <titleInfo>
    <title>How to make the world add up</title>
  </titleInfo>
  <titleInfo type="alternative">
    <title>How to make the world add up</title>
    <subTitle>ten rules for thinking differently about numbers</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Harford, Tim</namePart>
    <namePart type="date">1973-</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  <typeOfResource>text</typeOfResource>
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    <place>
      <placeTerm type="text">London</placeTerm>
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    <publisher>The Bridge Street Press</publisher>
    <dateIssued>2020</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>338 p.</extent>
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  <abstract>When was the last time you read a grand statement, accompanied by a large number, and wondered whether it could really be true? Statistics are vital in helping us tell stories, we see them in the papers, on social media, and we hear them used in everyday conversation and yet we doubt them more than ever. But numbers, in the right hands, have the power to change the world for the better. Contrary to popular belief, good statistics are not a trick, although they are a kind of magic. Good statistics are not smoke and mirrors; in fact, they help us see more clearly. Good statistics are like a telescope for an astronomer, a microscope for a bacteriologist, or an X-ray for a radiologist. If we are willing to let them, good statistics help us see things about the world around us and about ourselves, both large and small, that we would not be able to see in any other way. In How to Make the World Add Up, Tim Harford draws on his experience as both an economist and presenter of the BBC's radio show 'More or Less'. He takes us deep into the world of disinformation and obfuscation, bad research and misplaced motivation to find those priceless jewels of data and analysis that make communicating with numbers worthwhile. Harford's characters range from the art forger who conned the Nazis to the stripper who fell in love with the most powerful congressman in Washington, to famous data detectives such as John Maynard Keynes, Daniel Kahneman and Florence Nightingale. He reveals how we can evaluate the claims that surround us with confidence, curiosity and a healthy level of scepticism. Using ten simple rules for understanding numbers plus one golden rule this extraordinarily insightful book shows how if we keep our wits about us, thinking carefully about the way numbers are sourced and presented, we can look around us and see with crystal clarity how the world adds up.</abstract>
  <tableOfContents>Introduction : how to lie with statistics -- Rule one. Search your feelings -- Rule two. Ponder your personal experience -- Rule three. Avoid premature enumeration -- Rule four. Step back and enjoy the view -- Rule five. Get the back story -- Rule six. Ask who is missing -- Rule seven. Demand transparency when the computer says 'no' -- Rule eight. Don't take statistical bedrock for granted -- Rule nine. Remember that misinformation can be beautiful too -- Rule ten. Keep an open mind -- The golden rule. Be curious.</tableOfContents>
  <note type="statement of responsibility">Tim Harford.</note>
  <note>Published in the USA by Riverhead Books, 2021 as: The data detective :  ten easy rules to make sense of statistics.</note>
  <note>Includes bibliographical references and index.</note>
  <subject>
    <topic>Statistics</topic>
    <topic>Methodology</topic>
  </subject>
  <subject>
    <topic>Social sciences</topic>
    <topic>Statistical methods</topic>
  </subject>
  <subject>
    <topic>Statistics</topic>
  </subject>
  <classification authority="lcc">HA29 .H3339 2020</classification>
  <identifier type="isbn">9781408712245 (hardcover)</identifier>
  <identifier type="isbn">1408712245 (hardcover)</identifier>
  <identifier type="isbn">9781408712238 (paperback)</identifier>
  <identifier type="isbn">1408712237 (paperback)</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">210113</recordCreationDate>
    <recordIdentifier source="OCoLC">on1180241851</recordIdentifier>
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