Recently, we had a client come to us with (among other things) the following question: Who is more valuable, Customer Type A, or Customer Type B? This client already tracked the net profit and loss generated by every customer who used his services, and had begun to analyze his customers […]
In the previous installment of the Statistics to English Translation, we discussed the technical meaning of the term ”significant”. In this installment, we look at how significance is calculated. This article will be a little more technically detailed than the last one, but our primary goal is still to help […]
In this installment of our ongoing Statistics to English Translation series1, we will look at the technical meaning of the term ”significant”. As you might expect, what it means in statistics is not exactly what it means in everyday language. As always, a pdf version of this article is available […]
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 […]
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. […]
“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 […]
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 […]
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 […]
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.
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.”