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The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty

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3.81  ·  Rating Details ·  265 Ratings  ·  20 Reviews
A must-read for anyone who makes business decisions that have a major financial impact. As the recent collapse on Wall Street shows, we are often ill-equipped to deal with uncertainty and risk. Yet every day we base our personal and business plans on uncertainties, whether they be next month's sales, next year's costs, or tomorrow's stock price. In The Flaw of Averages, Sa ...more
Hardcover, 392 pages
Published June 1st 2009 by John Wiley & Sons (first published May 13th 2009)
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Blakely
Dec 06, 2012 Blakely rated it really liked it
If you've read this book you'll find it quite ironic that I'm giving it a rating of 4. A real rating of the book would look like this:


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Abe Farag
Aug 21, 2015 Abe Farag rated it it was amazing
loved this book. For my it was really eye opening to see so many ways that well intention-ed management direction could result in such poor operational outcomes. So many project management decisions and directions when designing new hardware, software, or physical products are related to asking for and executing strategy related to guesses about the future. The Flaw of averages spells out some common pitfalls in those guesses.
In my experience managing product design projects in for technology a
...more
Fvandrog
Oct 23, 2013 Fvandrog rated it did not like it
I was tremendously disappointed with this book. I got the false impression that it would focus on statistics in all aspects of life -- instead it is on discussing business cases, which makes it rather boring. In addition, statistical principles are discussed in very lay terms, without any of the actualy interesting mathematical details.
Mattia Battiston
Fantastic Read! Whenever faced with uncertainties use distributions and simulations, not averages.

I work in IT - software development - and I've always had to deal with plans and estimates. This book explains with extreme clarity why the traditional way of using averages for such reasons is wrong in so many ways!

I already knew the saying that you're not meant to use averages as they are wrong half the time, but this book still opened my eyes on the real reasons behind it.
Some of my favourite qu
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Brad Felix
May 17, 2015 Brad Felix rated it it was amazing
I'd recommend this book to anyone who works for a corporation that uses numbers.

In my professional experience, I've found that managers often ask for your best prediction on some uncertain outcome and when you try to explain all the underlying variables and distributions of those variables that could influence the outcome - they typically reply with an incredulous "Give me a number!" Without a sophisticated way to model or simulate the results, most analysts are left to finding the average of h
...more
Vadim
Mar 17, 2015 Vadim rated it it was ok  ·  review of another edition
Эта без сомнения умная книга написана столь же хорошо, сколько и утомительно. Глава за главой автор уговаривает нас не делать действительно распространенную ошибку: полагаться в наших планах на средние значения. Хотя тот, кто идет по середине дороги с двусторонним движением, не пострадает, пьяница, который идет по середине лишь "в среднем", будет "в среднем" же мертв. В общем, нужно думать не про средние значения (в среднем у каждого человека одно яичко и одна грудь, но это бессмыслица), а на ди ...more
Syed Ashrafulla
Sam Savage's flaw in the Law of Averages is roughly two-fold: dependence between variables and nonlinearity in the payoff. He forgets about the big one (small samples & non-Gaussianity kill the law), but that's not where I soured. I soured with his cutesy attempt to make probability accessible to everyone. I just don't like SIPs and SLURPs and whatever else is being used to just describe realizations of a random variable.

I understand, statistics is in my expertise, so I'm a bit biased. But c
...more
Rohit
Dec 15, 2012 Rohit rated it liked it
The book is a great introduction to some simple concepts of flaw of averages. The first half of the book does a great job in explaining the flaws of averages such as Jensen's inequality and some application of these flaws in real life. However the author keeps on repeating the same concept over and over again throughout the book in different domains such as finance, operations and trading. Most of the concepts covered in the book would be covered theoretically in the undergraduate statistics cou ...more
Tom
Sep 29, 2010 Tom rated it liked it
I usually called averages 'the curse of the average' because what does average really tell you without knowing the distribution shape? How often do people add averages (oops, unless the sample size is coincidentally the same).

The author advocates 'probability management' and creating a model that will run random tests using selected probability distribution functions.

The book's points are very good. Some one familiar with the 'theory of constraints' (like in The Goal, or It's Not Luck, or Crit
...more
Whitfield
May 24, 2010 Whitfield rated it it was amazing
Currently, a tectonic shift is occurring in the way statistics, probability, and simulations are being used for making decisions in the face of uncertainty. With this book, Professor Savage has captured a few of the core elements of this shift, has provided some history, and has pointed towards some future directions. Given how dry these topics can be, he has done well to make the book approachable and entertaining.

While the book meanders a bit, its principles are powerful. Interactive simulatio
...more
Gary
Nov 16, 2013 Gary rated it it was amazing
This is a great book - if you want to understand why humans are almost always wrong when they make estimates. Dr. Savage looks at the way statistics has been and is being taught and points out how the advent and now common use of the digital computer makes much of the current pedagogy obsolete. Likewise, he offers real, applied examples of how variance and risk assessment can and are being used.

I enjoyed this book enough that I've given copies to a number of colleagues, clients, and business as
...more
Brandon Carlson
Mar 26, 2014 Brandon Carlson rated it liked it
Was excited about this one. It has some good points about how using averages is a good way to fail and how using probabilities and Monte Carlo simulations produce better results, but it just didn't wow me all that much. It came highly recommended from others and, possibly would have been better had I not read "How to Measure Anything" first. Seems to be a bit of overlap between the two. The author tries to steer us away from big words used in statistics to make people sound smart, but found that ...more
Enrique
Mar 27, 2013 Enrique rated it it was amazing
Woah,

It's an eerie yet comforting feeling reading people discuss this book. I had the chance of working on a research project and take a course by this professor. Good book, especially for the layperson, (which although we like to pretend we're not,we all are inside). Good basic concepts and the big take away is that life is a distribution, never settle on a number. :)
John
Apr 11, 2010 John rated it liked it
I only gave it 3 stars because of the lack of structure. The book starts out great --- then meanders into interesting, yet not so cohesive sections. However, I really like the concepts presented and think there's quite a bit of value to this approach. I recommend (especially the first half) to anyone that deals with making decisions in the face of uncertainty.
Kortney Korthanke
This book was required reading for an MBA class. The information was good...relevant to the the class. However, I feel the information could be said fewer words...much fewer. If you are a numbers and statistics person you may find all the supporting evidence fascinating. I was wishing there were Cliffs Notes.
Kelly
Jan 18, 2012 Kelly rated it liked it
This was a super worthwhile read. It is a highly accessible read and is very thought provoking. Highly recommended. So much so that I'll read it again in short order to ensure the concepts are connected to the seat of my pants (a metaphor from the book, which you'll have to read to understand...).
Tracey
Feb 16, 2010 Tracey rated it liked it
An interesting book about how much averages show up in our everyday world, and how often they are not a good number to follow. Not the best book about such things, the narrative is not as engaging as something like "Freakanomics". But the information about the stockmarket is very interesting.
Vicky
Dec 10, 2012 Vicky rated it liked it
This book is very intriguing, it is a challenge to understand and twice I stopped reading and tried to resume. I believe that the concept of averages and the concept of probability are very relevant to our everyday life. I wish I had more time for this book and plan to go back to it.
Jeremy Karmel
A good review of basic mistakes business make when doing market analysis. The basic insight is that profit at the average sales is not the same as the average profit given a sales distribution.
Ben Royal
An introduction to portfolio analysis that all investors need to know something about.
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Sam L. Savage is a Consulting Professor of Management Science and Engineering at Stanford University, and a Fellow of the Judge Business School at the University of Cambridge.
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“The five stages of model development. —Donald Knuth, Stanford computer scientist Knuth discovered that computer program development goes through five stages. These steps also apply to building models, and I rigorously adhere to them in my consulting work. 1. Decide what you want the model to do. 2. Decide how to build the model. 3. Build the model. 4. Debug the model. 5. Trash stages 1 through 4 and start again, now that you know what you really wanted in the first place. Once you realize that step 5 is inevitable, you become more willing to discard bad models early rather than continually to patch them up. In fact, I recommend getting to step 5 many times by building an evolving set of prototypes. This is consistent with an emerging style of system development known as Extreme Programming.2 To get a large model to work you must start with a small model that works, not a large model that doesn’t work. —Alan Manne, Stanford energy economist” 0 likes
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