63 books
—
3 voters

Goodreads helps you keep track of books you want to read.

Start by marking “The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty” as Want to Read:

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

by

**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 Wiley
(first published May 13th 2009)

## Friend Reviews

To see what your friends thought of this book,
please sign up.

## Reader Q&A

To ask other readers questions about
The Flaw of Averages,
please sign up.

Be the first to ask a question about The Flaw of Averages

The best risk related books: finance, mathematics, probability, fractals and nonlinear dynamics

More lists with this book...

## Community Reviews

Showing 1-30

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

5 xxxxxxxxx

4.5 xxxxxxxxxxx

4 xxxxxxxxxxxxx

3.5 xxxxxxxxxxxxxxx xxx

3 xxxxxxxxxxxxxxxxxxxxxxx xxxxxxxx

2.5 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

2 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

1.5 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

1 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

0.5 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

0 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

start of book end o ...more

I understand, statistics is in my expertise, so I'm a bit biased. But come ...more

I feel like the core theory of the book could have probably been explained in a long form blog post. It's not a particula ...more

**Don’t just check the book’s score; check the variability of it too**

This is an excellent and mostly easy to read book on common traps we fall in by guiding our decisions using a single figure, mostly the average of the variable of interest. The examples given make the flaws become vivid. Prof Savage introduces several memorable terms in English, making it more efficient to share ideas on uncertainty. The terms that contradicted the beginnings of the book are SIP and SLURP; difficult to remember. I ...more

Anyone who makes ANY business decision should know some statistics and could make good use of this book. It helps to know math, but you don't have to to get the points in the book.

I liked the chapters about options and the "mindles" most. The cha ...more

A great book. ...more

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 ...more

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

In my experience managing product design projects in for technology a ...more

While the book meanders a bit, its principles are powerful. Interactive simulatio ...more

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

I enjoyed this book enough that I've given copies to a number of colleagues, clients, and business as ...more

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. :) ...more

There are no discussion topics on this book yet.
Be the first to start one »

## News & Interviews

Need another excuse to treat yourself to a new book this week? We've got you covered with the buzziest new releases of the day.
To create our...

27 likes · 5 comments

No trivia or quizzes yet. Add some now »

“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”
—
1 likes

More quotes…