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4 points

·
30th Jun 2020

I just finished my M.S. in statistics. Make sure you have these undergraduate-level topics nailed:

Linear Algebra (first semester, say at the level of Lay's text - look at it on Amazon to get an idea for its topics), down cold. Assume that you will get no time to review this material in class.

Calculus - have integration and differentiation techniques down cold from Calc. I and II, including Taylor/Maclaurin series. Double integration, partial derivatives, and Lagrange multipliers from Calc. III.

Real Analysis - make sure you can do ε-δ proofs as if they are second nature. Limits, continuity, uniform continuity, pointwise convergence, uniform convergence.

Probability and mathematical statistics, at the level of Wackerly's text.

Any programming experience you have would be helpful: doesn't matter if it's C, C++, Java, Python, or R. You have a CS degree, so this should be well covered.

1 point

·
28th Jul 2022

Linear Algebra and it's applications by David Lay here

1 point

·
10th Jan 2019

There's some use of it in your precal book. I used this book in class for linear algebra and physics research to try to generalize and combine ideas.

1 point

·
3rd Sep 2017

Cool.

**Linear Algebra** Don't waste your time with anything other than Lay, pretty much. Sounds like you're 100% new to LinAlg (it's not about polynomial equations) so it may be a bit tough to get off the ground working by yourself, but not impossible. It'd be worth finding a MOOC on the subject, there should be plenty. Otherwise, it's a pretty standard freshman maths course and a lot of people struggle with it (not because it's hard, just because it's *different* to HS maths), so there's a ton of resources on the internet.

**Calculus** Kinda just gotta slog away with where you're at tbh. I had Stewart as a freshman, didn't think it was overly great though. Still, that's the kind of level you need, so search for "alternatives to Stewart calculus" and anything that comes up should be appropriate. I wouldn't be able to tell you which to pick though.

**Stats** Basically, completing both of the above is pretty much a prerequisite for being able to understand linear regression properly, so don't expect to gain much by diving straight into stats. You could probably find a "business analytics" style textbook that would let you do more stats without understanding what's really going on under the hood, but if you want to stick with it in the long term you'll benefit more from getting stuff right at the beginning.

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