Comment by yiransheng | Hacker News Reader

Comment by yiransheng | Hacker News Reader

In my opinion, one big reason in the fall of statistics is the asymmetry in curriculum.

If you are in CS/Machine Learning, you will be forced/suggested to take a few statistics/probability courses, typically up to a regression course. These are good enough to get you started and familiar with statistical concepts and methodology.

However, if you come from a typical statistics program, programming/computing courses are almost always never required. Professors in probability theory/statistics often do not have great computing skill, they might know enough to get around in R/Mathlab, and teach you the basics in these tools, but a lot of times you are left in the dark in terms learning how to code.

If your career goal is an analyst, whose job is report oriented, you can get by by knowing just enough R (SAS, Matlab etc.) scripting. As your deliverables are generally fancy LaTex pdf (or presentations). But current job market pays and values more of a "data scientist", whatever that terms mean. This type of roles typically requires solid software engineering background, and requires you to be able to work with software developers and commit to the same codebase on a regular basis. The lack of programming/computing skills of a stats majored students will be a huge minus for this type of responsibilities.

Granted, I started college 30+ years ago, so my perspective may be outdated, but I fear that it might not be. What you say about "asymmetry" struck me because it seems like a more widespread issue. Some anecdotes from my college years:

* The CS students did all of their work on the college mainframe, and there was a pervasive attitude that personal computers were toys.

* The earliest adopters of PC's, and of using computers to solve problems rather than as objects of study, were in the physics department.

* Math required students to learn programming, but only one course used it -- numerical analysis.

I wonder if doing symbolic math by hand still dominates math education. Of course I enjoy doing it as a form of recreation, but I think that my use of math in my subsequent career would be stunted, had I not taken an interest in programming outside of the math department.

I also wonder if "the hot stuff in discipline A is being taught in department B" is just a feature of the chaotic nature of scholarship and research, meaning that a student needs to explore more than one field in order to really be top notch in their main chosen field.

> Professors in probability theory/statistics often do not have great computing skill, they might know enough to get around in R/Mathlab, and teach you the basics in these tools, but a lot of times you are left in the dark in terms learning how to code.

Hah, as a random anecdote, I had a graduate random processes class (from the Math department) last quarter where for one of the homework problems in his solution the professor basically used an Excel spreadsheet as a for loop. I was completely dumbfounded.

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