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From Stanford's admissions page:

My mathematics background isn't that strong. Should I still apply?

A strong mathematics background, especially in probability, statistics and linear algebra, is important in the admission process. However, it is not the only factor that determines which applicants are admitted. You may consider strengthening your math background and applying later, or just hope that factors such as breadth or research experience will compensate for a relatively weak math background.

My math background isn't "weak" per se, but I assume they are talking about a much stronger level of mathematics than I might have on the gradesheets of my MS and bachelor's programmes. I do take an interest in mathematics, and I try to study several concepts related to stats and math (eg., Machine Learning).

However, how can I prove this? I have done well in courses related to Machine Learning and Probability, and have taken courses in Real Analysis and Linear Algebra (and there is of course overlap in all four of those areas), but how can I say "I also read stuff because I like it"? I guess one way would be to ask a professor in the stats dept. to guide me through some research and then make them assess me, but how else can I show that I have "strengthened my background"?

Also, is a background in machine learning, signal processing and computer science in general considered for these admissions?

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You can take the math subject GRE and do well and send them the results, assuming they accept them. There’s nothing like a good score on that exam to convince the committee you know the math.

In my view, one of the best uses of the subject GRE is to make up for shortcomings elsewhere in your application.

  • Thanks for the reply! I have considered it, but I'm also concerned because it has stuff like topology, which I'm not entirely familiar with. – learning Oct 7 '17 at 14:05
  • Also, is a background in machine learning, signal processing and computer science in general considered for these admissions? – learning Oct 7 '17 at 14:19
  • Machine learning especially is considered relevant and helpful for statistics programs these days, however I don’t know if that’s what they mean by “a math backhand.” – Lev Reyzin Oct 7 '17 at 14:21
  • For background they were clear that they need probability, linear algebra, real analysis. I have taken courses in all (and they're all used in ML), but maybe not at the level they expect, and probably not as many. I also took a few more "core" statistics and mathematics courses but didn't do all that well. That's yet another reason why I want to know how I can show my improvement. – learning Oct 7 '17 at 14:31
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    Also, the subject GRE doesn't really have topology on it, so that shouldn't be a worry. – Lev Reyzin Oct 8 '17 at 1:42

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