I bought an Android phone, nothing fancy just my first foray in the smartphone world, which is a big change coming from the dumb phone world(*). Everything is different and I am back at being a newbie; this is what … Continue reading →

R news and tutorials contributed by (552) R bloggers

I bought an Android phone, nothing fancy just my first foray in the smartphone world, which is a big change coming from the dumb phone world(*). Everything is different and I am back at being a newbie; this is what … Continue reading →

Teacher: “How variable is your estimate of the mean?” Student: “Uhhh, it’s not. I took a sample and calculated the sample mean. I only have one number.” Teacher: “Yes, but what is the standard deviation of sample means?” Student: “What do you mean means, I only have the one friggin number.” Statisticians have a habit

One of the most straightforward examples of how we use Bayes to update our beliefs as we acquire more information can be seen with a simple Bernoulli process. That is, a process which has only two possible outcomes. Probably the most commonly thought of example is that of a coin toss. The outcome of tossing

As September draws nearer, my mind inevitably turns away from my lofty (and largely unmet) summer research goals, and toward teaching. This semester I will be trying out a teaching technique using live data collection and analysis as a tool to encourage student engagement. The idea is based on the electronic polling technology known as

I was pleasantly surprised to have my recreational reading about baseball in the New Yorker interrupted by a digression on statistics. Sam Fuld of the Tampa Bay Rays, was the subjet of a Ben McGrath profile in the 4 July 2011 issue of the New Yorker, in an article titled Super Sam. After quoting a minor-league...

One of my teaching roles is in an introductory Genetics course, where first year students are presented with a wide range of new ideas at a relatively fast pace. It seems that often, students choose to take a memorization approach to learning the material, rather than taking the chance to think about how and why

I’ve written a few times before about how to choose the software you work with, and what you should and should not care about when making those choices. I maintain a page with various resources related to this, if you’re interested, most notably the Emacs Starter Kit for the Social Sciences. A revised version of

In a recent post, I asked for suggestions for introductory R computing books. In particular, I was looking for books that: Assume no prior knowledge of programming. Assume very little knowledge of statistics. For example, no regression. Are cheap, since they are for undergraduate students. Some of my cons aren’t really downsides as such. Rather,

My sabbatical is rapidly coming to an end, and I have to start thinking more and more about teaching. Glancing over my module description for the introductory computational statistics course I teach, I noticed that it’s a bit light on recommend/background reading. In fact it has only two books: A first course in statistical programming