We describe the “the local to global principle.” It is a principle used to break algorithmic problem solving into two distinct phases (local criticism followed by global solution) and is an aid both in the design and in the application of algorithms. Instead of giving a formal definition of the principle we quickly define it and discuss a few examples and methods. We have produced both a stand-alone PDF (more legible) and a HTML/blog form (more skimable).

Continue reading The Local to Global Principle

## “I don’t think that means what you think it means;” Statistics to English Translation, Part 1: Accuracy Measures

Scientists, engineers, and statisticians share similar concerns about evaluating the accuracy of their results, but they don’t always talk about it in the same language. This can lead to misunderstandings when reading across disciplines, and the problem is exacerbated when technical work is communicated to and by the popular media.

The “Statistics to English Translation” series is a new set of articles that we will be posting from time to time, as an attempt to bridge the language gaps. Our goal is to increase statistical literacy: we hope that you will find it easier to read and understand the statistical results in research papers, even if you can’t replicate the analyses. We also hope that you will be able to read popular media accounts of statistical and scientific results more critically, and to recognize common misunderstandings when they occur.

The first installment discusses some different accuracy measures that are commonly used in various research communities, and how they are related to each other. There is also a more legible PDF version of the article here.

## Google AdSense Channels IDs and the Cramer Rao Inequality

“Comparing Apples and Oranges: Two Examples of the Limits of Statistical Inference, With an Application to Google Advertising Markets” is our analysis of Google AdSense Channel IDs and our use of the Cramer Rao bound to show that these IDs fundamentally limit what participants in the Google online advertising market can measure (and therefore in turn limit what these players can do).

Continue reading Google AdSense Channels IDs and the Cramer Rao Inequality

## What is the gambler’s equivalent of Amdahl’s Law?

While executing some statistical detective work for a client we had a major “aha!” moment and realized something like “Amdahl’s Law” rephrased in terms of probability would solve everything. We finished our work using direct methods and moved on. But it is an interesting question: what is the probabilist’s (or gambler’s) equivalent of Amdahl’s Law? Continue reading What is the gambler’s equivalent of Amdahl’s Law?

## Survive R

New PDF slides version (presented at the Bay Area R Users Meetup October 13, 2009).

We at Win-Vector LLC appear to like R a bit more than some of our, perhaps wiser, colleagues ( see: Choose your weapon: Matlab, R or something else? and R and data ). While we do like R (see: Exciting Technique #1: The “R” language ) we also understand the need to defend oneself against the abuse regularly dished out by R. Here we will quickly share a few fighting techniques.

Continue reading Survive R

## A Discrete Model Gauging Market Efficiency

New paper: A Discrete Model Gauging Market Efficiency PDF

We *highly* recommend reading the PDF version, but please find below a HTML translation of the paper.

We follow up on some interesting work from the literature and explore some conditions that allow large predatory traders to dominate markets.

## Good Graphs: Graphical Perception and Data Visualization

What makes a good graph? When faced with a slew of numeric data, graphical visualization can be a more efficient way of getting a feel for the data than going through the rows of a spreadsheet. But do we know if we are getting an accurate or useful picture? How do we pick an effective visualization that neither obscures important details, or drowns us in confusing clutter? In 1968, William Cleveland published a text called *The Elements of Graphing Data,* inspired by Strunk and White’s classic writing handbook *The Elements of Style* . *The Elements of Graphing Data* puts forward Cleveland’s philosophy about how to produce good, clear graphs — not only for presenting one’s experimental results to peers, but also for the purposes of data analysis and exploration. Cleveland’s approach is based on a theory of graphical perception: how well the human perceptual system accomplishes certain tasks involved in reading a graph. For a given data analysis task, the goal is to align the information being presented with the perceptual tasks the viewer accomplishes the best. Continue reading Good Graphs: Graphical Perception and Data Visualization

## A Demonstration of Data Mining

REPOST (now in HTML in addition to the original PDF).

This paper demonstrates and explains some of the basic techniques used in data mining. It also serves as an example of some of the kinds of analyses and projects Win Vector LLC engages in. Continue reading A Demonstration of Data Mining

## On The Hysteria Over “The Cloud”

On The Hysteria Over “The Cloud”

The frenzy of anticipation and opinion about “The Cloud” is so intense and so pointless it becomes “parody proof.”

Continue reading On The Hysteria Over “The Cloud”

## Should your mom use Google search?

Today’s question is: “should your mom use Google search?” It it is a good thing that Google has directly told us that their motto is “don’t be evil,” as their systems are subtle and difficult to evaluate.