tonym9428

According to the math department at UIUC, student wanting to gain admission to the MS program should have completed up to the following courses. "It is strongly recommended that the entering student has taken courses that cover the syllabi of the following: Math 417 - Introduction to Abstract Algebra Math 418 - Advanced Linear Algebra Math 447 - Real Variables A course in computer programming" Here's the link: http://www.math.uiuc.edu/GraduateProgram/masters/mastmath.html#ms_math

What are you interested in? Pure, Applied, I'm not a math student, but you'll definently have quite a few pre-requisites to take before gaining admission to a masters program in math especially since you've only taken calc-1 If you really want that math degree, consider going to school full time and getting a BS in mathematics. Since you worked at a hedge fund, you might have some savings, so live on that. You'll probably have to take some proof based math courses before admission also. Have you thought about a masters in financial engineering or a masters in quantitative finance....You'll still have quite a few math pre-reqs to take with both options, but it will likely be less.

I have a BA and MA in political science. The only math that I took as an undergrad was calc 1, calc 2, and elementary linear algebra...so yeah, I need to take a lot of math courses. In grad school, I had stats courses on linear regression, logistic regression, statistical computing with R, multilevel modeling, etc...but the mathematical theory was often ignored. For example, in one of my classes, we used John Fox's "Applied Regression Analysis and Generalized Linear Models", which is pretty dense, but we rarely touched on the mathematical theory behind dummy variables, interaction terms, statistical modeling, etc. Unfortunately, I'll be pursuing my second Bacheor's at a school which doesn't have a stats department (Univ of Kansas). They have a math department and supposedly offer some mathematical stats courses, but it doesn't seem to be a priority.

In my other post, I mentioned that I recently finished my MA and was considering returning to school in order to take some math courses so that I can apply for graduate programs in statistics. Do you think it would be beneficial to just head back and work on a second bachelor degree in computer science? While I know a few programming languages, I'm not interested in programming as a career. I just want to work with statistical modeling and data visualization of large data sets. I'm also intrigued by some of these computational math and computational science programs.

I was just wondering what would be a better undergraduate degree to prepare for work in "data science". Statistics, computer science, applied maths, physics, etc. I asked this question on flowing data also: http://forums.flowingdata.com/topic/data-science

Here's the NYT article: http://www.nytimes.com/2009/08/06/technology/06stats.html?_r=1

Obviously no one has predict precisely what the job market will be like, but will there be a demand for statisticians 10 years from now. I remember reading a NYT article in which they stated that statistics was the "it'" degree this decade....and I was just curious if that trend would continue.

This is the big issue for me. I never wanted to be in school past the age of 25, but I'm at a point where I want to continue working in the analytics field, but just don't feel that I'm as prepared. Sure, I've been doing freelance work with no problem, but a lot of this is child's play...I just need more education to further my employment goals. I'm very cautious of being perceived as a career student. At this stage, I'm fine as I got my undergrad, then went straight to grad school, and got out. However, there's a point when an individual can be labeled a career student and that hampers their future goals....or at least it seems so to me. At 25, I'm still young, so maybe I should try and get this all done by the time I'm 30.

Thank you for the response. I recently talked to a statistics prof at Columbia and they reccomended that I also take real analysis....is that also necessary? or just for the top schools? I don't necessarily need to go to a top 20 school, so not too concerned about rankings and stuff like that. I'm noticing that the math pre-req's for biostats department are much less...why? less theoretical? After some research, I'm now considering returning to school full time to just get a BS in mathematics...will take 2-3 years.

I recently completed my master's degree in political science. Since then, I've been working and doing some freelance analytics work using R, Python, MySQL, etc. Most of the analytics work I do is rather simple descriptive statistics, but I also do OLS and logit/probit regression analysis....a lot of my clients are more interested in my web scraping services, but that's neither here nor there. I've been considering returning to school to pursue a MS in Statistics. I don't want to get a second bachelors degree, but plan on taking the required pre-req's for grad programs in statistics. I was considering taking the following classes. As an undergrad, I took Calc 1, calc 2, and linear algebra, but need to retake both courses as it's been a while. MATH 104 = Pre-Calculus MATH 121 = Calculus 1 (after M-104) MATH 122 = Calculus 2 (after M-121) MATH 223 = Vector Calculus (after M-122) MATH 290 = Elementary Linear Algebra (after M-122) MATH 320 = Applied Differential Equations (after M-223 andM-290) MATH 526 = Applied Mathematical Statistics 1 (after M-122) MATH 590 = Linear Algebra 1 (after M-223 and M-290) MATH 591 = Linear Algebra 2 (after M-290) MATH 605 = Applied Regression Analysis (after M-526) MATH 627 = Probability (after M-223 and M-290) It will take me three to four years before I can apply to a grad program. I may even go to school part time. Does anyone have any suggestions?