## Living in A Lognormal World

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 […]

## Statistics to English Translation, Part 2b: Calculating Significance

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 […]

## Statistics to English Translation, Part 2a: ’Significant’ Doesn’t Always Mean ’Important’

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 […]

## “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. […]

## 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 […]

## 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 […]

## 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.

## Exciting Technique #1: The “R” language.

Our first “exciting technique” article is about a statistical language called “R.” R is a language for statistical analysis available from http://cran.r-project.org/ . The things you can immediately do with it are incredible. You can import a spreadsheet and immediately spot relationships, trend and anomalies. R gives you instant access […]