I want this course in the catalog at my university. Way better than “critical thinking” or “research methods.”

# Category: quantitative scholarship

## When Bayesian Statistics Broke into History

Wonderful article here about the Mosteller and Wallace analysis of the twelve Federalist Papers, the ones of disputed authorship–was it Madison or Hamilton who wrote them? With a nice, easy-to-understand explanation of the Bayesian methodology they used.

## Calculus as a Microagression

Yesterday I was cautioned by the recounting of an event that occurred in our College of Business. It seems that a lecturer was explaining a concept that required either averaging or the area under a curve, and resorted to writing an integral on the board, by way of illustration. This was NOT a demonstration of technique, nor an explanation of how to perform calculations required in the course, rather just background. However, one student–correctly recalling that calculus was not a prerequisite–took umbrage; he wrote a letter of complaint to the Dean! Holy hellfire sh!t! Just last week I spent 10 minutes explaining to my calculus-averse biostatistics students how the standard normal table was constructed (integration does not conquer all). I had no idea I was skating so close to the edge. Probably because I’m an idiot or a lunatic.

## How many significant figures should I use?

That question gets asked dozens of times every semester in my statistics classes; it’s pretty clear that most of my students have no sense of scale or proportion about numbers.

But now I have Dr Rhett Alain’s short answer in his Dot Physics Measurement and Uncertainty Smackdown, wherein he refers to the (extremely) long answer in John Denker’s excellent Uncertainty as Applied to Measurement and Calculation. Why we’re not teaching this in our service courses for science majors, I have no idea. The Monte Carlo approach described by Alain is a simple application of what statisticians call “bootstrapping,” so perhaps I will start.

*Second hand tip from the Geek Press*

## How to become a stats-savvy boss…

…in one easy lesson. Go read Alan Downey’s slide presentation “How to be a good consumer of statistical analysis.”

Then get yourself some data and start working on those CDF plots.

## The Sad Story of p-values

Wow, it’s jackpot week for statistics videos. I just found this treasure explaining p-values.

## (Some) Scientists are Frickin’ Liars

Tom Naughton explains the difference between an observational study and a clinical trial, in terms everyone can understand.

I’m SO stealing this lecture for my biostatistics courses.

*Tip from Authority Nutrition via Gary Jones (who you really should be reading).*