This post is by Eric.
On August 15, I will be teaching this two-week course offered by the PRIISM center at NYU. The initial plan was to offer it to the NYU students entering the A3SR MS Program, but we are opening it up to a wider audience. In case you don’t like clicking on things, here is a short blurb:
This course aims to prepare students for the Applied Statistics for Social Science Research program at NYU. We will cover basic programming using the R language, including data manipulation and graphical displays; some key ideas from Calculus, including differentiation, integration, and optimization; an introduction to Linear Algebra, including vector and matrix arithmetic, determinants, and eigenvalues and eigenvectors; some core concepts in Probability including random variables, discrete and continuous distributions, and expectations; and a few simple regression examples.
This is a paid class, but Jenniffer Hill, who runs the program, tells me that department scholarships are available based on program and student needs.
If you would like to take a course, we ask that you fill out a short survey here. (If you need financial assistance, please indicate it under “Is there anything else you’d like to share with us?” survey question.) You can register here. We are planning to offer it in-person at NYU and online via Zoom.
Warning: This is my first time teaching this class, so I am not sure how much material we will be able to cover. We will have to gauge that as we go.
If you have taught something like this before and have suggestions for me, please leave those in the comments.
I’ve taught something like this before (a variety of stats classes at various levels), and that looks like an enormous amount of material to try to cover in two weeks. I mean, it looks like an enormous amount to cover in a semester.
As for suggestions, I would suggest paring it down dramatically. Maybe just focus on some basic R and distributions?
Thanks. This is more of a boot camp situation than a traditional class, but I get your point. We will see how it goes.
With just 2 weeks it’s unlikely students will get much out of this unless they have covered most of the material previously.
However, these days they don’t really need to develop much skill in the techniques as the computer can do the maths. So they mostly just need to pick up the vocabulary and language of the maths used in statistics, at least at this point.
Also, especially for he first time through, it’s hard to beat the advice of mostly just do what the previous instructors did.
Thanks, Keith.
Keith
Really? That sounds safe to me and also the easiest way. But “hard to beat” hopefully involves quality. Assuming that what previous instructors did was high quality sounds like poor advice to me. If we approached introductory statistics like that, well… many do, and see what you get.
Not ideal but without a first time through (the selection of material and students that take such a course) it’s unlikely one will happen across something better.
I’m a little confused by the description and the comments. There is a lot to cover here, but if the focus is on some basic R programming, then it seems like the scope of the course – “basic math, probability, and statistics skills” – is essentially equivalent to basic programming skills. Conceptual thinking about math, probability, and statistics is a worthy goal. I doubt that 2 weeks of programming really does anything towards that goal (perhaps a bit overstated – surely it does “something” but I’d say not much). Does basic R programming really contribute to this basic understanding? It may (arguably) be necessary for mastery, but I don’t see it as necessary or sufficient for a basic understanding. And, with 2 weeks, it hardly seems the place to start. What it does provide, is a concrete set of skills that could be used for basic mathematical and statistical reasoning, but it seems to skip the step of developing the basic reasoning. From the description, I think a more accurate title would be “Basic R Programming for Mathematics and Statistics.”