John Myles White

After a recent Wordpress upgrade took my site down for an indefinite length of time, I decided to finish migrating this site to a static site generator.

As a graduate student, I came to love working with the roll call voting data sets that have been compiled for the United States Congress by political scientists like Keith Poole and Howard Rosenthal.

Over the last couple of years, I’ve seen a large number of people attempt to diagnose the quality of their randomized experiments by looking for imbalances in covariates, because they expect covariate imbalances to be ruled out by successful randomization.

Introduction Link to heading Yesterday, Uri Simonsohn published a blog post called “Interactions in Logit Regressions: Why Positive May Mean Negative”.

I recently reread Yarkoni and Westfall’s in-progress paper, “Choosing prediction over explanation in psychology: Lessons from machine learning”.

I broadly believe that the statistics community would benefit from greater exposure to computer science concepts.

Today I saw a claim being made on Twitter that 17% of Jill Stein supporters in Louisiana are also David Duke supporters.

The other day a friend posted the following old joke about the level of rigor that mathematicians usually require.

I just found a minimal example of how easy it is to confuse R’s CSV parser when providing it with ill-formatted data.

Deriving Distributions from Distances Link to heading Several of the continuous univariate distributions that frequently come up in statistical theory can be derived by transforming distances into probabilities.

In my experience, people seldom appreciate just how much more compelling a 5-sigma effect is than a 2-sigma effect.

The Big Message Link to heading People sometimes use \(R^2\) as their preferred measure of model fit.

Yesterday, a coworker pointed me to a new paper by Jacob Westfall and Tal Yarkoni called “Statistically controlling for confounding constructs is harder than you think”.

Introduction Link to heading One of the things that set statistics apart from the rest of applied mathematics is an interest in the problems introduced by sampling: how can we learn about a model if we’re given only a finite and potentially noisy sample of

Over the last few months, I’ve had a lot of conversations with people about the use of winsorization to deal with heavy-tailed data that is positively skewed because of large outliers.

Introduction Link to heading Although I’ve recently decided to take a break from working on OSS for a little while, I’m still as excited as ever about Julia as a language.

Lately, I’ve been rereading a lot of Meehl’s papers on the epistemological problems with research in psychology.

Introduction Link to heading Several months ago, I promised to write an updated version of my old post, “The State of Statistics in Julia”, that would describe how Julia’s support for statistical computing has evolved since December 2012.

1st Normal Form: The database contains at least one table that is an exact copy of another table, except with additional columns. 2nd Normal Form: The database contains at least one table that is a corrupt, out-of-date copy of another table, except with a…

Many newcomers to Julia are confused by the seemingly dissimilar behaviors of the following two functions: julia> a = [1, 2, 3] 3-element Array{Int64,1}: 1 2 3 julia> function foo!

tl;dr Link to heading Please do not use arithmetic on data.frame objects when programming in R.

Introduction Link to heading I just got home from JuliaCon, the first conference dedicated entirely to Julia.

Here are two hypothetical conversations about psychological research.

Introduction Link to heading A recent thread on Theoretical CS StackExchange comparing the Johnson-Lindenstrauss Lemma with the Singular Value Decomposition piqued my interest enough that I decided to spend some time last night reading the standard JL pap…

Introduction Link to heading It may be old news to some, but I just recently discovered that the automatic type inference system that R uses when parsing CSV files assumes that data sets will never contain 64-bit integer values.

Correction: One problem with the argument I make below is that password storage length isn’t actually relevant if websites hash passwords instead of storing them in plaintext.

Introduction Link to heading Some people have come to believe that Julia’s vectorized code is unusably slow.

For many of the people I talk to, Julia’s main appeal is speed.

To celebrate my last full month on the East Coast, I’m doing a bunch of talks.

As a fun side project last night, I decided to implement a basic package for working with Hopfield networks in Julia.

A few days ago I disabled the comment system on this site.

The last two weeks have been full of changes for me.

Introduction Link to heading In my last post, I described how we can derive modes, medians and means as three natural solutions to the problem of summarizing a list of numbers, \((x_1, x_2, \ldots, x_n)\), using a single number, \(s\).

Introduction / Warning Link to heading Any traditional introductory statistics course will teach students the definitions of modes, medians and means.

A while back a friend asked me for advice about speeding up some R code that they’d written.

Today I saw an article on Hacker News entitled, “America’s CEOs Want You to Work Until You’re 70”.

A Brief Introduction to Metaprogramming in Julia Link to heading In contrast to my previous post, which described one way in which Julia allows (and expects) the programmer to write code that directly employs the atomic operations offered by computers, th…

When people try out Julia for the first time, many of them are worried by the following example: julia> factorial(n) = n == 0 ?

Introduction Link to heading A few months ago, Drew Conway and I gave a webcast that tried to teach people about the basic principles behind linear and logistic regression.

Having spent all five of my years as a graduate student trying to get psychologists and economists to agree on basic ideas about decision-making, I think the following two pieces complement one another perfectly: Cosma Shalizi’s comments on rereading Blan…

One of these days I am going to finish my series on problems with how NHST is issued in the social sciences.

Updated 12.2.2012: Added sample output based on a suggestion from Stefan Karpinski.

[Updated 10/18/2012: Fixed a typo in which mantissa was replaced with exponent.]

What do you think when you see a model like the one below?

One Paragraph Summary Link to heading Always explore your data visually.

Four years after I first noticed it, Finder still has a bug in it that causes it to report a negative number of items waiting for deletion:

Introduction Link to heading Statistically-trained readers of this blog will be very familiar with the Central Limit Theorem, which describes the asymptotic sampling distribution of the mean of a random vector composed of IID variables.

The Quick-and-Dirty Summary Link to heading I was recently asked to participate in a proposed SXSW panel that will debate the question, “Will Data Scientists Be Replaced by Tools?”

As some of you may know already, I’m co-organizing an upcoming conference called DataGotham that’s taking place in September.

Recently a few members of R Core have indicated that part of what slows down the development of R as a language is that it has become increasingly difficult over the years to achieve consensus among the core developers of the language.