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Guesstimates

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Guesstimates
Some solutions for the book “Guesstimation” by Weinstein & Adam
Anton Antonov antononcube@gmail.com http://www.linkedin.com/pub/anton-antonov/7/879/89a

Introduction
In this notebook (article) I have shown the solutions of some problems from the book “Guesstimation: Solving the World’s Problems on the Back of a Cocktail Napkin” by Lawrence Weinstein and John A. Adam. ( See http://www.amazon.com/Guesstimation-Solving-Worlds-Problems-Cocktail/dp/0691129495 .) I have followed the chapter structure of the book. I have copied the questions from the corresponding sections. I give my estimates and the ones produced and explained in the book. The most interesting part of this notebook (article) is the example and explanations I give of why using the geometric mean to estimate averages from lower and upper bounds estimates is adequate in many cases. See the sub-section “Geometric mean” in the next section. In the first chapter of the book the authors just explain a technique for quick computation of the geometric mean. They do not elaborate much on why it is a better estimate except by giving few examples. (I found their short description inspiring, so I looked for an explanation and other examples.)

1. How to Solve Problems ü Geometric mean I show in this sub-section an example of why it is better to use the geometric mean to calculate averages based on estimated minimum and maximum values. Suppose we have to estimate the mpg (miles per gallon) of the average car in US. (See problem “5.2 Drowning in gasoline“ below.) We can use the estimates 6 and 50 as the maximum and minimum mpg’s respectively. (The number 6 is for really old or antique cars; the number 50 is for Toyota Prius and the like.) Using the geometric mean we get 6 µ 50 º 17.3 to be the estimate of the average US car mpg. Now let us try to make a more informed estimate using mpg’s for variety

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