This page includes the most recent downloads for How To Measure Anything, 1st – 3rd Editions. Currently, downloads for the 1st and 2nd editions are still available. However, Doug Hubbard will soon be adding downloads for the 3rd edition to be released in the spring of 2014.
Book charts with directions including 2 Ed table
A summary of key charts and tables from the book including a new easy-to-read “population proportion” table for the second edition.
Chapter 5; Additional Calibration Questions
Additional calibration tests in case the tests in the book weren’t enough to get you fully calibrated.
Chapter 6; Monte Carlo, 2 Ed
A new spreadsheet with the original Monte Carlo example as shown in both the first and second edition of the book. This also includes the additional example with the “Contract Loss” risk as shown in the second edition of the book.
Chapter 6; Markov Simulations, 2 Ed
A new spreadsheet with the original Markov Simulation example as shown in both the first and second edition of the book.
Chapter 6; Distributions for 2 Ed
These are the new distributions mentioned in the second edition: Triangular, Beta, Power Law, and correlated normal distributions. Each provides an explanation as well as a random number generator for that distribution (which you can copy and paste for other simulations). The correlated normal distributions are two normal distributions that are correlated. The worksheet shows two ways to make a desired correlation happen.
Chapter 7 Information Value
This spreadsheet computes the Expected Value of Perfect Information (EVPI) for a simple binary example, an example based on a normal distribution, and one based on a uniform distribution. This improved version separates the uniform from the normal instead of computing them on the same worksheet so that the two different methods are easier to understand.
Chapter 9 Sampling Examples
This shows several examples from chapter 9 where we compute 90% confidence intervals with small samples, population samples with catch & recatch, sampling in experiments and a simple regression model. This includes a correction to the regression example in the 2nd edition.
Chapter 10 Bayesian Inversion Examples
This is the detailed calculation for the Bayesian inversion for continuous quantities using the example shown in the book. The table is shown in the first edition but I streamlined the second edition by removing some of these details from the book and just teaching the general principles.
How To Measure Anything: Conference Presentation 2007
This is a PowerPoint presentation about the book which I often give at conferences with an IT emphasis. It may be hard to follow without the oral presentation but those who listened to the presentation might want to have a copy.
White Paper: Applied Information Economics
This is an overview of AIE. It is written primarily for IT managers but the points can apply to anyone. It compares AIE to traditional ROI and weighted scores.