Robert Sedgewick has the slides for a talk, Algorithms for the Masses on his web site.

My favorite slide is the one titled “O-notation considered harmful” — Sedgewick observes that it’s more useful to say that the running time of an algortihm is ~aN^c (and back this up with actual evidence from running the algorithm) than to have a theorem that it’s O(N^c) (based on a model of computation that may or may not be true in practice).

The serious point of the talk, though, is that everyone should learn some computer science, preferably in the context of intellectually interesting real-world applications. This is what Sedgewick is doing in his Princeton course and in his book with Kevin Wayne, Algorithms, 4th edition, which I confess I have not read. There’s a Coursera course, in six-week parts, starting in August and November respectively. For a lot of…

At any R Q&A site, you’ll frequently see an exchange like this one:

Q: How can I use a loop to […insert task here…] ?
A: Don’t. Use one of the apply functions.

So, what are these wondrous apply functions and how do they work? I think the best way to figure out anything in R is to learn by experimentation, using embarrassingly trivial data and functions.

If you fire up your R console, type “??apply” and scroll down to the functions in the base package, you’ll see something like this:

Let’s examine each of those.

1. apply
Description: “Returns a vector or array or list of values obtained by applying a function to margins of an array or matrix.”

OK – we know about vectors/arrays and functions, but what are these “margins”? Simple: either the rows (1), the columns (2) or both (1:2). By “both”, we mean “apply the…

People who want to learn the very basics of R may find these videos made by some Berkeley grad students useful.