# Is it just me? Or…

…are you, too, getting tired of being jerked around by folks from a really bad neighborhood? Continue reading Is it just me? Or…

Skip to content
# The Home for Wayward Statisticians

## In a time of universal surveillace, privacy is a revolutionary act.

# Category: Statistics at UTSA

# Is it just me? Or…

# R Tutorial: A Bayesian Estimate of Proportion

# R Tutorial: Teasing Out a Markov Chain

# Beginning: R Tutorials

# New Tricks for this Old Dog

# A fair 3-way choice using coin tosses

# Heretics! Burn them!

# A short tale about the long tail

# Brace yourself for (re)apportionment!

# Hey, I’m not (too) crazy!

…are you, too, getting tired of being jerked around by folks from a really bad neighborhood? Continue reading Is it just me? Or…

This is an old chestnut in Bayesian statistics, using the conjugate beta prior to find a beta posterior distribution for a proportion. If you’re unfamiliar with the calculation of the posterior distribution, there’s a link in the tutorial. Continue reading R Tutorial: A Bayesian Estimate of Proportion

Azzalini and Bowman’s Old Faithful geyser data provides fodder for a lot of data exploration in R (scatterplots, ggplot2, simple regression, kmeans clustering, and Markov chain estimation). All the really interesting stuff in the tutorial happens if you click through to Analysis > Models > Standardized Cluster Model. (The standardized clustering approach is not given in the original paper.) Continue reading R Tutorial: Teasing Out a Markov Chain

After a long, slow start, R is catching on with statisticians and (some) scientists at UTSA. The Biology Department has asked that I use R in teaching biostatistics, and many of the courses for statistics majors are using R rather than SAS (a UTSA tradition). Students have not been idle; the statistics club has asked me to present an occasional series of R tutorials to get their members up to speed. Here are the first two tutorials: Getting Started with R The ggplot2 Fakebook These tutorials are all HTML files, generated with RMarkdown. Students who attend the presentations are also … Continue reading Beginning: R Tutorials

Udacity is offering an introductory statistics course this summer, beginning June 25th. I’ve enrolled, to see how the Big Boys do it. This is going to put a lot of pressure on traditional universities–especially here in Texas, where we’re busily hammering out the $10,000 Bachelor’s degree. I figure if I don’t get up with the leaders of the buffalo herd, I’m gonna get trampled or left behind. Tip from Meep at the Conservative Commune. Continue reading New Tricks for this Old Dog

I’d like to make a fair and random choice among 3 alternatives, but the only randomizing device I have available is a coin to toss. Worse yet, I suspect the coin may be biased. What to do? Continue reading A fair 3-way choice using coin tosses

Just as UTSA begins to ramp up its Quantitative Scholarship program to inject mathematical reasoning into every crevice of our curriculum, heretics are beginning to doubt the whole enterprise. Part of the problem is that most remedial and math literacy programs (and textbooks) are filled with bullshit applications and examples (“the rate at which the fluid level in a martini glass will go down”, etc.) that suggest the authors never worked an honest lick in their lives. Very few people need calculus, but darn near everyone could benefit from knowing the basics of things like the critical path method — … Continue reading Heretics! Burn them!

Lingustics Log has a nice post about early papers on long tail distributions. Good dissertation material, thanks guys! Continue reading A short tale about the long tail

Here’s a concise history of congressional apportionment, with a good stab at explaining the mathematical rules involved. Tannenbaum’s Excursions in Modern Mathematics devotes a chapter to the topic; I used to teach this in our statistical literacy course. Tip from The Geek Press Update (22 July). A new book on voting systems is reviewed in the New Yorker. Continue reading Brace yourself for (re)apportionment!

Looks like I’m not the only one who’s thinking about having students read some of the classics in statistics, see here and here! Even more classical goodies in the tip from Andrew Gelman. Continue reading Hey, I’m not (too) crazy!