StatsGuy92

I don't have much experience on the job as I just finished my undergrad and I am starting a Gradutate program in Statistics (geared towards data mining/machine learning) as well in the Fall, but from my own research and reading through a lot of program's curriculums, I would say your list is pretty extensive and complete. If I were to add anything to your list, it would be Natural Language Processing. Yes it is somewhat more related to computer science, but anyone who can handle statistical machine learning can definitly handle it. If you plan on going into industry, I've been told this course is one of the most useful in data science for many fields of applications. I am planning on taking this class during my second semester of the grad program.

I am in the exact same situation as you OP, i.e. I am satistified with all of my application except my GRE score; my verbal was not as high as I had wished...

I have no idea what the standards are for top EU programs as I am only applying in NA, but you have very extensive coursework as well as a great extra curricular resume. And so unless you have posted an inaccurate summary of your background, I would think that you would be competitive anywhere you would apply, including top programs. GL.

For the 16-40 PhD programs, your GRE is more than sufficient. You won't have any problems getting into these programs. But if you aim for top programs, although your score is not that bad, you should probably retake it given your MATH/STAT/COMP coursework is not that extensive. Best of Luck, StatsGuy92.

Yeah I've taken Numerical analysis a few semesters ago and I would say that it is rather unimportant/irrelevant in probability/statistics. Basically you learn different algorithms to approximate the solution of non-linear equations or complicated differential equations, but nowadays most of these calculations are done by any standard computer package with mathematical applications (even Excel!). Numerical analysis is probably most important for people who study computer science with a concentration on the computational aspects of software.

Hey StatFall2014, Thanks for responding! I will definitly look into UCSB, and possibly a few others as a safety (although I am almost certain to attend U of T if I don't get admission in my targets). Judging from your experience, is my concern that I go to a "non-target" undergraduate institution founded, or if the coursework/program is rigorous, it doesn't matter at all? Or is it somewhere in between? StatGuy92.

Anyone? Would I be competitive for these US programs?

Hi all, I am aware of how irritating these profile evaluation threads can be, but I need advice regarding my chances in getting into PhD programs in Statistics (Fall 2015). Undergrad Institution: Canadian University Program: BSc, Mathematics and Computational Finance GPA: 3.85 (w/ 2 semesters left) Type of Student: White Male Quantitative Coursework: Actuarial Mathematics and Computational Finance: Actuarial Math. I, Actuarial Math II, Math. of Finance, Stochastic Calculus for Finance I [grad], Stochastic Calculus for Finance II [grad]. Mathematics Coursework: Advanced Calculus I & II, Linear Algebra I & II, Numerical Analysis, Operations Research, Analysis I & II, ODE, Graduate Real Analysis [grad], Measure Theory [grad], PDE [grad]. Statistics Coursework: Probability I & II, Statistics, SAS Programming, Linear Models, Advanced Probability Theory [grad], Stochastic Processes [grad], Time Series [grad], Simulation [grad]. Computer Science: Intro. to Programming, Object-Oriented Programming I & II, Data Structures and Algorithms. Finance (from my University's Business School): Theory of Finance I & II, Options and Futures, Advanced Derivatives Markets. (*Note that prior to entering University, I went through the 2-year CEGEP (French-Canadian) system where we do preparatory courses. I was in the "Pure and Applied Science" program. My quantitative preparatory coursework: Calculus I-III, Intro. to Lin. Algebra, Intro to Diff. Equations, Intro to Prob. and Stats, Mechanics, Waves and Optics, Electricity and Magnetism, Modern Physics, Intro. to Programming, Chemistry of Solutions I & II, General Biology.) Research/Work Experience: I do not have any research experience, but have a personal project where I am writing from scratch a software to analyze financial time series. I am also in a co-op program and had 2 internships as an actuarial programmer in a consulting firm and had some exposure to (equity) market research for my second internship. I am also completing a C++ Programming Certificate for Financial Engineering (@ a US University). Awards/Honors/Recognitions: I was nominated for the co-op student (of the year) award. Never applied for any scholarship so far. Letters of Recommendation (3): 1 from my program director (PhD in Stats), 1 from a Stats professor (PhD in Stats from Berkeley) and 1 from a computational finance teacher I had (PhD in Math. Finance) GRE Scores: TBD (Taken next October) __________________________________________________________________ So basically this is pretty much my profile. The American (PhD Stats) programs I am interested in are the following: Columbia, NYU, Cornell and Berkeley. (These programs are very active in math. finance and do research in what I am the areas I am interested) My main concern are that my University is not particularly well known and that it might affect me. I looked up a lot of profiles of students from these schools and most came from either well-known US programs or from top schools in China. Although this is the case, of the class that graduated from my program last year, I know that 1 went on to Princeton to do a master in finance and another to Columbia to do an MFE (master in Financial Engineering) as the undergraduate coursework we go through is very rigorous and only 15 students in my program are admitted each year. My drop-back plan if I dont get admitted to these schools is to do my graduate studies at the Univ. of Toronto as they have a strong department in Statisics and I am nearly certain I would get admitted (for the MS at least, and eventually to the doctorate). But I would hope that some of you who have gone through the whole Stats-PhD admission process (or who have been in admission committees for such programs) could give me an honest evaluation of my profile. I apologize for the long post and look forward to your assessments, Thank you!