Normal Deviate

Statisticians are woefully ignorant about computer science (CS).

And computer scientists are woefully ignorant about statistics.

O.k. I am exaggerating. Nonetheless, it is worth asking: what important concepts should every statistician know from computer science?

I have asked several friends from CS for a list of the top three things from CS that statisticians should know. While there wasn’t complete agreement, here are the three that came up:

  1. Computational complexity classes. In particular, every statistician should understand what P and NP mean (and why you get $1,000,000 from the Clay Mathematics Institute if you prove that $latex {P\neq NP}&fg=000000$.). Understanding the fact that searching through all submodels in a variable selection problem is NP hard will convince you that solving a convex relaxation (a.k.a. the lasso) is a really good idea.
  2. Estimating computing time. In CS and machine learning, it is expected that one will estimate the number of operations…

Lihat pos aslinya 149 kata lagi


Tinggalkan Balasan

Isikan data di bawah atau klik salah satu ikon untuk log in:


You are commenting using your account. Logout / Ubah )

Gambar Twitter

You are commenting using your Twitter account. Logout / Ubah )

Foto Facebook

You are commenting using your Facebook account. Logout / Ubah )

Foto Google+

You are commenting using your Google+ account. Logout / Ubah )

Connecting to %s