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I am a junior in college studying business and I have a 2.8 GPA right now. I have low grades and I am thinking about either getting into a masters program for applied statistics to be a statistician or a master's degree in data analysis or finance. However, I might have messed up because I got a few C grades in my early math classes and I had to withdraw from Calculus 1 twice. I took it the third time and got a B+. I understand that I screwed up badly but I am thinking about changing my life around. I have a bunch of W grades and I am thinking about trying to at least get into a masters program for higher education. I don't want to end up a failure. Be honest, do I have a chance at all or should I get another bachelor's degree in a field that's well-paying? I am ready to try my hardest to succeed.
Institution: National Technical University of Ukraine (top 1-2 in country) Major(s): BS Economic Cybernetics which is equal to Mathematical Economics/Econometrics in EU Minor(s): N/A (we don't have major/minor system) GPA: 94/100 local system; approx. 3.96/4.00 US GPA scaled; 5.75/6.00 Swiss scaled; 1.45 German Type of Student: International White Female GRE General Test: Q: 160 V: 148 W: N/A (no results yet) Languages: English - CAE Certificate (199/grade B); German - Goethe C1 Zertifikat (71/100) Programs Applying: Statistics/Quant Finance/Data Science MS Research Experience: several published research papers in native language, 1 in English related to Quant Finance combined with DS methods Awards/Honors/Recognitions: diploma with honors (highest recognition you can get in Ukrainian universities), top 10-15% of class Pertinent Activities or Jobs: 3-month internship, followed by position in Data Science field (current) Letters of Recommendation: I understand that the reputation of professors from my country should be taken with a grain of salt, but their LORs are likely to be strong. 1st LOR should be from my bachelor thesis mentor and 2nd one from my bachelor/master courses with high reputation in data science/stats field. Math/Statistics Grades: Grading system and subject names are different from US/European ones, but I can try covert them into those standards if needed. Any Miscellaneous Points that Might Help: A vast amount of DS/ML courses taken on Coursera (yeah, I know, kind of questionable), Kaggle contributor/expert (good for DS program, not sure about Stats). Planning to continue research in Quant Finance field. My experience is not strictly Statistics oriented, but also including Data Science, Econometrics and Quant Finance. My bachelor program had strong Stats/Math/Econometrics and mediocre Computer Science/Data Science subjects, however I am still not sure how those subjects will be evaluated by those universities. Applying to master programs at: Target: ETH Zurich (most desirable) UZH/University of Zurich (desirable too) Safety: LMU Munich TUM Munich The main question is, should I retake GRE? I have high GPA, but I got it in mediocre university (in terms of world reputation), so this might not be enough. How will such weak verbal GRE score affect my chances of admission, even though I have sufficient proof of English (and even German which is not mandatory) by standards of mentioned universities. There is still time for me to retake GRE, but I am not sure if it is necessary. I also should point out that target country for me is Switzerland because of family relocation plans, whereas Germany seems to be less desirable, but safer option. ETH Zurich Stats MS is top 1 option for me, but any other master program mentioned above at ETH would be satisfactory too. Which areas should I improve in my case? Can I boost my chances by getting more research experience? Any help would be appreciated🙂
Hello, I’m a current MS student in Math (expected graduation Spring 2020) applying to PhD programs in Statistics for Fall 2020 and am looking for feedback on my tentative school list - apologies if this is posted in the incorrect place or manner! Undergraduate Institution: Top 10 US public university Graduate Institution: Local state school Majors: Economics GPA: Undergrad 3.96, Grad 4.00 Type of student: White female Relevant Courses: Undergraduate: · Introduction to Statistics (A+), Econometrics (A), Applied Econometrics (A) · Calculus I -III , Linear Algebra and Differential Equations (A) · Proof writing (A) · Intro Mathematical Probability , Mathematical Statistics I, II (A) · Advanced Calculus I, II (Real Analysis I, II) (A) · Abstract Algebra, Number Theory, Advanced Linear Algebra (A) · Numerical Analysis (A) Graduate: · Topology (A) · Measure Theory (A) · Multivariate Statistics (A) · Computational Statistics (IP) · Calculus on Manifolds (IP) GRE General: Q170 (96), V170 (99), AW5.5 (98) GRE Subject: I really don’t want to take it! Research Experience: Year long project in probability, presented at a conference, summer project in machine learning presented at a big conference and papers submitted (but I probably won’t hear back in time), current thesis in regression methods for complex data structures (being as vague as possible here because it’s pretty niche). Work Experience: Two years at a think tank, supervisor on a Math REU, instructor of undergrad mathematics (labs and lectures). Honors and Awards: a bunch of university based awards. Letters: All from Math/Stats professors, all but one of whom I’ve done research with. I expect them to be very strong. Interests: Are varied – causal inference, algebraic statistics, machine learning, anything with good theoretical meat. Concerns: I don’t have any formal training in Computer Science, but I’ve done extensive work in Python, Matlab, R (mostly R). I’m having a hard time narrowing my schools down based on research interest, since there’s so much I’ve enjoyed – all I know is that I don’t want Biostats. Am at any kind of disadvantage having an MS already? I know there are many undergrads who have about as much graduate math as I do, but my undergrad was in another field. Schools: I am obviously biased towards CA. All programs are Statistics PhD’s unless otherwise indicated. · Reach: Berkeley, Harvard · Target: NCSU, Duke, UCLA, UC Davis · Safe: UCSB, UCI, UCSD (Dept of Math and Statistics), JHU, Colorado State Questions about schools: According to US News, UCI is ranked 50th, but looking around here I’m seeing it referred to as a strong program. What am I missing? I wish I had a more realistic “reach”, but I’m very geographically biased. Suggestions? Thank you!
· Hi all, I've been a lurker on here for a while, and I wanted to get a better gauge about what schools I can/should apply to for a PhD in either Statistics or Operations Research. I'm interested in statistical simulation problems that arise naturally in Actuarial Science. On a more practical side, I am interested in bringing the simulation and statistical techniques from Financial Engineering to Actuarial Science. I’d love to hear your thoughts. EDUCATION: o Major: Actuarial Science and Mathematics with a minor in Computer Science from University of Wisconsin o GPA: 3.73 overall, 4.0 in Actuarial Science classes, ~3.8 in Math classes o Relevant Courses: Calc III (AB), Intro to Probability (A), Proof-based Linear Algebra (AB), Stochastic Processes (A), Real Analysis I (AB), Stochastic Calculus (AB), Mathematical Statistics (A), Intro to Computer Science (A), Actuarial Mathematics I and II (both As), Loss Models (A), Interest Theory (A) o Currently in Linear Programming, Numerical Analysis, Real Analysis II, Regression, and Data Structures o I plan to take Measure Theory and possibly an Integer Optimization course next semester RESEARCH/RELEVANT ACTIVITIES: o Currently involved in a research project with an Actuarial Science professor comparing Machine Learning methods with more traditional GLM as applied to Actuarial Science. I oversee the coding (in R) and the conceptual picture for the ML side of the work. We will likely not have a paper until the end of the school year. o Programming: Proficient in R, MATLAB, and Java o Two actuarial internships, one at a smaller life insurance company, another at a bigger property/casualty company doing insurance claim modeling in R using Markov Chains. o I've also graded for two different Actuarial Science classes, and tutored introductory Statistics and Calculus, as well as passed three actuarial exams. GRE/Letters of Rec: o GRE: 164Q, 162V, waiting on writing o I have one excellent letter of rec from an Actuarial Science professor who I have graded for and who I am working with. Two other letters of rec, one from a professor I am taking a class with now and took a class with last semester who knows I am a good student, another Stats professor who I had a class with who I have asked for help with graduate school. Likely that they might not be particularly stellar except for the first one. Schools: Statistics PhD: o University of Wisconsin o UC-Berkeley o Duke o Wharton o John Hopkins o UNC-Chapel Hill INSTORE o CMU Operations Research PhD: o Columbia IEOR o Princeton ORFE o Stanford OR (dream school) o Cornell OR Do I have a chance at these schools I've listed? Is it too top heavy? What should I add/take off? Also, should I retake the GRE? I really don’t want to if I don’t have to…. But I will if my chances are far too low.