Tim Harford - How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers

By Tim Harford

The Undercover Economist

The Logic of Life

Dear Undercover Economist

Adapt

The Undercover Economist Strikes Back

Messy

Fifty Things that Made the Modern Economy

The Next Fifty Things that Made
the Modern Economy

How to Make the World Add Up

Tim Harford

THE BRIDGE STREET PRESS

First published in Great Britain in 2020 by The Bridge Street Press

Copyright Tim Harford 2020

The moral right of the author has been asserted.

All rights reserved.

No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of the publisher, nor be otherwise circulated in any form of binding or cover other than that in which it is published and without a similar condition including this condition being imposed on the subsequent purchaser.

A CIP catalogue record for this book is available from the British Library.

ISBN 978-1-4087-1222-1

The Bridge Street Press

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Little, Brown Book Group

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To teachers everywhere, and my teachers in
particular; in fond memory of Peter Sinclair

The truly genuine problem... does not consist of proving something false but in proving that the authentic object is authentic.

UMBERTO ECO

Y ou know the old story about storks delivering babies?
Its true.

I can prove it with statistics.

Take a look at the estimated population of storks in each country, and then at the number of babies born each year. Across Europe, theres a remarkably strong relationship. More storks, more babies; fewer storks, fewer babies.

The pattern is easily strong enough to pass a traditional hurdle for publication in an academic journal. In fact, a scientific paper has been published with the title Storks Deliver Babies (p = 0.008). Without getting too technical, all those zeros tell us that this is not a coincidence.

Perhaps you have already guessed the trick. Large European countries such as Germany, Poland and Turkey are home to many babies and many storks. Small countries such as Albania and Denmark have few babies and few storks. While theres a clear pattern in the data, that pattern does not mean that storks cause babies to appear.

You can prove anything with statistics, it seems even that storks deliver babies.

Youd certainly have got that impression from reading How to Lie with Statistics. Published in 1954 by a little-known American freelance journalist named Darrell Huff, this wisecracking, cynical little book immediately received a rave review from the New York Times and went on to become perhaps the most popular book on statistics ever published, selling well over a million copies.

The book deserves the popularity, and the praise. Its a marvel of statistical communication. It also made Darrell Huff a nerd legend. Ben Goldacre, an epidemiologist and bestselling author of Bad Science, has written admiringly of how The Huff had written a ripper. The American writer Charles Wheelan describes his book Naked Statistics as an homage to Huffs classic. The respected journal Statistical Science organised a Huff retrospective fifty years after its publication.

I used to feel the same way. As a teenager, I loved reading How to Lie with Statistics. Bright, sharp, and illustrated throughout with playful cartoons, the book gave me a peek behind the curtain of statistical manipulation, showing me how the swindling was done so that I would not be fooled again.

Huff is full of examples. He begins by pondering how much money Yale graduates make. According to a 1950 survey, the class of 1924 had an average income of close to $500,000 a year in todays terms. That is just plausible enough to believe this is Yale, after all but half a million dollars a year is a lot of money. Is that really the average?

No. Huff explains that this improbably salubrious figure comes from self-reported data, which means we can expect people to exaggerate their income for the sake of vanity. Furthermore, the survey is only of people who bothered to respond and only those alumni that Yale could find. And who are easily found? The rich and famous. Who are the little lost sheep down in the Yale rolls as address unknown? asks Huff. Yale will keep track of the millionaire alumni, but some of the also-ran graduates might easily have slipped through the net. All this means that the survey will present a grossly inflated view.

Huff briskly moves on through a vast range of statistical crimes, from toothpaste advertisements based on cherry-picked research to maps that change their meaning depending on how you colour them in. As Huff wrote, The crooks already know these tricks; honest men must learn them in self-defense.

If you read How to Lie with Statistics, you will come away more sceptical about the ways numbers can deceive you. Its a clever and instructive book.

But Ive spent more than a decade trying to communicate statistical ideas and fact-check numerical claims and over the years, Ive become more and more uneasy about How to Lie with Statistics and what that little book represents. What does it say about statistics and about us that the most successful book on the subject is, from cover to cover, a warning about misinformation?

Darrell Huff published How to Lie with Statistics in 1954. But something else happened that very same year: two British researchers, Richard Doll and Austin Bradford Hill, produced one of the first convincing studies to demonstrate that smoking cigarettes caused lung cancer.

Doll and Hill could not have figured this out without statistics. Lung cancer rates had increased six-fold in the UK in just fifteen years; by 1950 the UK had the highest in the world, and deaths from lung cancer exceeded deaths from tuberculosis for the first time. Even to realise that this was happening required a statistical perspective. No single doctor would have formed more than an anecdotal impression.

As for showing that cigarettes were to blame again, statistics were essential. A lot of people thought that motor cars were the cause of the rise in lung cancer. That made perfect sense. In the first half of the twentieth century, motor cars became commonplace, with their exhaust fumes and the strangely compelling vapour from the tar in new roads. Lung cancer increased at the same time. Figuring out the truth that it was cigarettes rather than cars that caused lung cancer required more than simply looking around. It required researchers to start counting, and comparing, with care. More concisely, it required statistics.