The flaw of averages: why we underestimate risk in the face of uncertainty
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ
Wiley
2009
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references (p. 371-381) and index |
| Beschreibung: | XXII, 392 p. Ill. 24 cm |
| ISBN: | 9780471381976 0471381977 |
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| 245 | 1 | 0 | |a The flaw of averages |b why we underestimate risk in the face of uncertainty |c Sam L. Savage |
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Datensatz im Suchindex
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|---|---|
| adam_text | Titel: The flaw of averages
Autor: Savage, Sam L.
Jahr: 2009
Contents
Preface xv
Acknowledgments xix
Introduction Connecting the Seat of the Intellect to
the Seat of the Pants 1
You cannot learn to ride a bicycle from a book,
and I claim the same is true for coping with
uncertainly. Paradoxically, this book attempts to do
what it claims is impossible.
FOUNDATIONS
Part 1 The Big Picture 9
Chapter 1 The Flaw of Averages 1
In planning for the future, uncertain outcomes are
often replaced with single, so-called average numbers.
TTiis leads to a class of systematic errors that I call
the Flaw of Averages, which explains among other
things why forecasts are always wrong.
Chapter 2 The Fall of the Algebraic Curtain
and Rise of the Flaw of Averages 22
The electronic spreadsheet brought the power of
business modeling to tens of millions. In so doing,
it also paved the way for an epidemic of the Flaw
of Averages.
vii
viii Contents
Chapter 3 Mitigating the Flaw of Averages 26
New technologies are illuminating uncertainty
much as the lightbulb illuminates darkness.
Probability Management is a scientific approach to
harnessing these developments to cure the Flaw
of Averages.
Chapter 4 The Wright Brothers Versus
the Wrong Brothers 34
The success of the Wright Brothers airplane was
the result of carefully constructed models that they
tested in their wind tunnel. Analogous models can
help us manage uncertainty and risk, but as we
saw in the financial crash of 2008, models can
also be used to obfuscate.
Chapter 5 The Most Important Instrument
in the Cockpit 40
The proper use of models, like the instruments in
an airplane, is not obvious.
Part 2 Five Basic MINDIes for Uncertainty 45
Chapter 6 MINDIes Are to MINDs What HANDIes
Are to HANDS 49
Just as industrial designers develop handles
to help us grasp the power of physics with our
hands, informational designers develop Mindles
(first syllable rhymes with mind ) to help us grasp
the power of information with our minds. Section 2
will provide some important Mindles for grasping
uncertainty.
Chapter 7 Mindle 1: Uncertainty Versus Risk 52
These two concepts are often used interchangeably
bvi they shouldn t be. Uncertainty is an objective
feature of the universe, whereas risk is in the eye of
the beholder.
Contents
ix
Chapter 8 Mindle 2: An Uncertain Number
Is a Shape 55
Even graduates of statistics courses have a hard time
visualizing uncertainty. A shape in the form of a
simple bar graph, called the histogram, does the trick.
Try running a simulation in your head or better yet,
on your web browser at FlawOfAverages.com.
Chapter 9 Mindle 3: Combinations of
Uncertain Numbers 67
When uncertain numbers are added or averaged,
the chance of extreme events goes down. I cover a
case study in the film industry.
Chapter 10 I Come to Bury gffiHA, Not to Praise it 78
Just as the height and weight of a criminal suspect
have been superseded by surveillance videos and
DNA samples, sigma is pushing obsolescence.
Chapter 11 Mindle 4: Terri Dial and the Drunk
in the Road 83
A banking executive discovers the Strong Form of
the Flaw of Averages: Average inputs don t always
result in average outputs. Designing an incentive
plan around your average employee is systematically
erroneous.
Chapter 12 Who Was Jensen and Why Wasn t
He Equal? 91
The Nuts and Bolts of the Strong Form of the Flaw
of Averages
This chapter shows how to identify the Flaw
of Averages before it occurs by understanding your
options and restrictions.
Chapter 13 Mindle 5: Interrelated Uncertainties 98
Interrelated uncertainties are at the heart of modern
portfolio theory. They are best understood in terms
of scatter plots.
x Contents
Part 3 Decisions and Information 109
Chapter 14 Decision Trees 111
Decision trees are a powerful Mindlefor thinking
through decisions in the face of uncertainty.
Chapter 15 The Value of Information 118
Because There Isn t Anything Else
The flip side of decision trees. Information is the
complement of uncertainty. What is it worth to
find things out?
Part 4 The Seven Deadly Sins of Averaging 127
Chapter 16 The Seven Deadly Sins of Averaging 129
So here are the Seven Deadly Sins, all eleven
of them. And the twelfth deadly sin is believing
we won t discover even more tomorrow.
Chapter 17 The Flaw of Extremes 133
Viewing uncertainties solely in terms of
nonaverage outcomes also leads to devastatingly
wrong answers and policy decisions.
Chapter 18 Simpson s Paradox 139
Imagine a weight loss treatment that makes people
lose weight on average, unless they are either male
or female, in which case it makes them gain
weight on average.
Chapter 19 The Scholtes Revenue Fallacy 142
Suppose you have various product lines with
different unit sales. The average unit sales times
the average profit per unit might be positive
while your average profit might be negative.
Chapter 20 Taking Credit for Chance Occurrences 147
If you execute a marketing campaign and make
a bunch of sales, how do you know the increase
wasn t just by chance?
Contents
x!
APPLICATIONS
Part 5 The Flaw of Averages in Finance 155
Chapter 21 Your Retirement Portfolio 157
If your retirement fund will last you 20 years
given average returns, then you are as likely
as not to suffer financial ruin before you
get there.
Chapter 22 The Birth of Portfolio Theory: The Age
of Covariance 163
Harry Markowitz started a revolution in finance
in the early 1950s by explicitly recognizing
risk/return trade-offs.
Chapter 23 When Harry Met Bill(y) 169
Bill Sharpe extended the work of Markowitz and
brought it into widespread practice.
Chapter 24 Mindles for the Financial
Planning Client 175
How the pros explain this stuff to their clients.
Chapter 25 Options: Profiting from Uncertainty 181
Options allow us to exploit uncertainty through
an understanding of the Strong Form of the Flaw
of Averages.
Chapter 26 When Fischer and Myron Met Bob:
Option Theory 192
The theory of three economists hi to the
trillion-dollar derivatives industry.
Chapter 27 Prices, Probabilities, and Predictions 200
The new phenomenon of prediction markets is
changing the way we perceive and report
uncertain events, such as political races.
xii Contents
Part 6 Real Finance 213
Chapter 28 Holistic Versus Hole-istic 215
When people invest in portfolios of oil exploration
sites, they often use the hole-istic approach. That
is, they rank the places to drill hole by hole, then
start at the top and go down the list until they
run out of money. This ignores the holistic effects
of portfolios.
Chapter 29 Real Portfolios at Shell 222
For several years, Shell has been using Probability
Management to manage its portfolios of petroleum
exploration sites in a more holistic manner.
Chapter 30 Real Options 228
An example of a real option is a gas well in
which you have the choice of whether or not to
pump depending on the price of gas.
Chapter 31 Some Gratuitous Inflammatory
Remarks on the Accounting Industry 236
You can t rely on accountants to detect risks
because generally accepted accounting principles
are built on the Flaw of Averages.
Part 7 The Flaw of Averages In Supply Chains 245
Chapter 32 The DNA of Supply Chains 247
The inventory problem introduced in Chapter 1 is
at the heart of all supply chains.
Chapter 33 A Supply Chain of DNA 254
When stocking out is not an option.
Chapter 34 Cawlfield s Principle 257
A manager at OUn creates a simulation to get ttvo
divisions of his organization to work as a team
and discovers a general principle in the process.
Contents xiii
Part 8 The Flaw of Averages and Some
Hot Button Issues 263
Chapter 35 The Statistical Research Group
of World War II 265
The exciting environment in which my father
became a statistician.
Chapter 36 Probability and the War on Terror 272
Two inescapable statistical trademarks of the war
on terror are the problem of fake positives and
implications of Markov chains.
Chapter 37 The Flaw of Averages and
Climate Change 289
The earth s average temperature may actually be
going down, not up, but you won t be happy
when you find out why. The Flaw of Averages
permeates this issue.
Chapter 38 The Flaw of Averages in Health Care 299
Treating the average patient is not healthy.
Chapter 39 Sex and the Central Limit Theorem 307
Women have a diversified portfolio of two
X chromosomes, whereas men have only one.
Apparently it makes a difference.
PROBABILITY MANAGEMENT
Part 9 Toward a Cure for the Flaw of Averages 317
Chapter 40 The End of Statistics as You Were
Taught It
The ninetheenth-century statisticians confirmed
their theories by simulating uncertainty with dice,
cards, and numbered balls. Today, computerized
dice, cards, and balls are bypassing the very
theories they were trying to confirm.
319
xiv Contents
Chapter 41 Visualization 324
Visual statistics provides a window into
distributions. You need to see it to appreciate it.
Chapter 42 Interactive Simulation: A New Lightbulb 328
Imagine simulating 100,000 rolls of a die before
your finger leaves the Enter key. A new technology
does for probability distributions what the
spreadsheet did for numbers.
Chapter 43 Scenario Libraries: The Power Grid 332
New data structures allow the results of simulations
to be added together like numbers, providing a more
practical approach to enterprisewide risk modeb.
Chapter 44 The Fundamental Identity
of SLURP Algebra 341
This looks like math. Feel free to skip it.
Chapter 45 Putting It into Practice 343
The technology surrounding Probability
Management is improvingfast, and recent
breakthroughs promises to make it more accessible
than ever.
Chapter 46 The CPO: Managing
Probability Management 354
The CPO must strike the correct balance between
transparency of presentation, data collection, and
statistical rigor.
Chapter 47 A Posthumous Visit by My Father 364
Some comments from the hereafter.
Red Word Glossary 367
Notes 371
About the Author 382
Index 383
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| spelling | Savage, Sam L. 1944- Verfasser (DE-588)139325700 aut The flaw of averages why we underestimate risk in the face of uncertainty Sam L. Savage Hoboken, NJ Wiley 2009 XXII, 392 p. Ill. 24 cm txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references (p. 371-381) and index Risk Uncertainty Entscheidungstheorie (DE-588)4138606-1 gnd rswk-swf Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd rswk-swf Risikomanagement (DE-588)4121590-4 gnd rswk-swf Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd rswk-swf Risikoanalyse (DE-588)4137042-9 gnd rswk-swf Statistische Entscheidungstheorie (DE-588)4077850-2 gnd rswk-swf Mittelungsverfahren (DE-588)4126019-3 gnd rswk-swf Entscheidungstheorie (DE-588)4138606-1 s Risikomanagement (DE-588)4121590-4 s DE-604 Entscheidung bei Unsicherheit (DE-588)4070864-0 s Risikoanalyse (DE-588)4137042-9 s Mittelungsverfahren (DE-588)4126019-3 s Wahrscheinlichkeitsrechnung (DE-588)4064324-4 s DE-188 Statistische Entscheidungstheorie (DE-588)4077850-2 s 1\p DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020342069&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Savage, Sam L. 1944- The flaw of averages why we underestimate risk in the face of uncertainty Risk Uncertainty Entscheidungstheorie (DE-588)4138606-1 gnd Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Risikomanagement (DE-588)4121590-4 gnd Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd Risikoanalyse (DE-588)4137042-9 gnd Statistische Entscheidungstheorie (DE-588)4077850-2 gnd Mittelungsverfahren (DE-588)4126019-3 gnd |
| subject_GND | (DE-588)4138606-1 (DE-588)4064324-4 (DE-588)4121590-4 (DE-588)4070864-0 (DE-588)4137042-9 (DE-588)4077850-2 (DE-588)4126019-3 |
| title | The flaw of averages why we underestimate risk in the face of uncertainty |
| title_auth | The flaw of averages why we underestimate risk in the face of uncertainty |
| title_exact_search | The flaw of averages why we underestimate risk in the face of uncertainty |
| title_full | The flaw of averages why we underestimate risk in the face of uncertainty Sam L. Savage |
| title_fullStr | The flaw of averages why we underestimate risk in the face of uncertainty Sam L. Savage |
| title_full_unstemmed | The flaw of averages why we underestimate risk in the face of uncertainty Sam L. Savage |
| title_short | The flaw of averages |
| title_sort | the flaw of averages why we underestimate risk in the face of uncertainty |
| title_sub | why we underestimate risk in the face of uncertainty |
| topic | Risk Uncertainty Entscheidungstheorie (DE-588)4138606-1 gnd Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Risikomanagement (DE-588)4121590-4 gnd Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd Risikoanalyse (DE-588)4137042-9 gnd Statistische Entscheidungstheorie (DE-588)4077850-2 gnd Mittelungsverfahren (DE-588)4126019-3 gnd |
| topic_facet | Risk Uncertainty Entscheidungstheorie Wahrscheinlichkeitsrechnung Risikomanagement Entscheidung bei Unsicherheit Risikoanalyse Statistische Entscheidungstheorie Mittelungsverfahren |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020342069&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT savagesaml theflawofaverageswhyweunderestimateriskinthefaceofuncertainty |