Everydata The Misinformation Hidden in the Little Data You Consume Every Day

225 Pages·2016·7.554 MB·English

by  John H. Johnson, Mike Gluck

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EVERYDATA
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EVERYDATA
The MisinforMaTion
hidden in The LiTTLe daTa
You ConsuMe everY daY
WhY Your gas Tank isn’T eMpTY,
You’re noT beTTer Than average, and
afriCa is bigger Than You Think
John h. Johnson, phd,
Mik e gLuCk
and
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First published by Bibliomotion, Inc.
39 Harvard Street
Brookline, MA 02445
Tel: 617- 934- 2 427
www.bibliomotion.com
Copyright © 2016 by John H. Johnson and Mike Gluck
All rights reserved. No part of this publication may be reproduced in any
manner whatsoever without written permission from the publisher, except in
the case of brief quotations embodied in critical articles or reviews.
Printed in the United States of America
Library of Congress Cataloging-in-Publication Data
Names: Johnson, John H., author. | Gluck, Mike, author.
Title: Everydata : the misinformation hidden in the little data you consume
every day / John H. Johnson, Mike Gluck.
Description: First Edition. | Brookline, MA : Bibliomotion, 2016.
Identifiers: LCCN 2015041504 (print) | LCCN 2016004445 (ebook) | ISBN
9781629561011 (hardback) | ISBN 9781629561028 (ebook) | ISBN 9781629561035
(enhanced ebook)
Subjects: LCSH: Econometrics. | Consumer behavior. | BISAC: BUSINESS &
ECONOMICS / Econometrics. | BUSINESS & ECONOMICS / Consumer Behavior. |
SOCIAL SCIENCE / Popular Culture. | BUSINESS & ECONOMICS / Decision-Making
& Problem Solving.
Classification: LCC HB139 .J636 2016 (print) | LCC HB139 (ebook) | DDC
646.7001/5195—dc23
LC record available at http://lccn.loc.gov/2015041504
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Dedicated to the memory of my mom, Elizabeth Johnson,
who read the newspaper with reckless abandon, always shared the
most fascinating research studies, and inspired my intellectual curiosity.
— John Johnson
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Contents
Foreword ix
Preface xi
1 Data, Data, Everywhere: An Introduction to Everydata 1
2 The Challenger Challenge: How Sampling Can
Affect Results 9
3 Red State Blues: Averages and Aggregates— A Closer
Look at Summary Statistics 27
4 Are You Smarter Than an iPhone- Using,
Radiohead- Loving Republican?: Understanding
Correlation Versus Causation 45
5 In Statistics We Trust: Is What You’re Seeing True? 65
6 Shrinking Africa: Misrepresentation and Misinterpretation 83
7 Spoonfed Data: When Cherry Picking Goes Bananas 105
8 Predicting Disaster: Forecasting the Future 123
9 It’s a Jungle Out There: Putting It All Together 143
Glossary 157
Notes 161
Index 193
Acknowledgments 203
About the Author 205
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Foreword
In the spring of 2010, the National Football League owners wanted,
among many other things, to extend the regular season by two games. As
executive director of the NFL Players Association (NFLPA), I knew this
was a bad idea. More games equal more injuries in a game that already
has a 100 percent injury rate. More injuries would mean more careers
cut short for athletes whose average careers are already just a little more
than three years. Our union faced serious concerns about player safety,
compensation, and how to protect the men who, every week during the
season, put themselves on the line in America’s most beloved sport.
Professional football is a multibillion-dollar industry— and grow-
ing. But in 2010–11, facing the first potential work stoppage in over a
decade, I needed a sure way to prove that the season needed to remain at
sixteen games.
I called John Johnson.
John is an expert on economics, statistics, and data, and he makes
even the most complicated data concepts seem simple and straightfor-
ward. In short, he is probably one of the smartest guys I know. He is able
to explain things carefully and thoughtfully and tailor his explanations
to the level of any audience and, most importantly, he’s never boring!
Like every football fan in America, the NFLPA wanted to save the
upcoming NFL season, so we gave John our data. John and his col-
leagues developed models that showed when and how often players
were injured. They identified the precise plays that had the most seri-
ous injuries (leading to the “kickoff rule,” which had a dramatic impact
on player safety). They estimated the potential economic losses from
extending the NFL season to eighteen games— using data to predict
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