Search the Community
Showing results for tags 'linear'.
Found 20 results
-
Hi, I am applying to programs in fall '22, with a range of target options (a few in top 10, a few in top 50, a few in top 150). My math background is weak. I work full-time so am trying to come up with an efficient plan that maximizes my chances for admissions. Math that I have: Calc 1 - AP Honors Calc 2 - B Linear Algebra - currently taking at Georgia State (likely A) Business stats - A Stats in public policy grad school - B Econometrics in public policy grad school - A Options that I am considering: 1. Take courses locally (mostly Georgia State University) Fall '21: Multivariable Calculus Spr '22: Stats 1 (in Math Dept), Differential Equations Sum ' 22: Stats 2 (in Math Dept) Fall '22: Linear Algebra with Real Analysis I - 23A (online at Harvard Extension) 2. Take courses online via Harvard Extension Fall '21: Multivariable calculus - 21A Spr '22: Mathematics for computation and data science - 23C Sum ' 22: Linear Algebra with Real Analysis I - 23A Fall '22: Mathematical Statistics 156 AND Differential Equations 21C Would love any advice. And open to other ideas too! Thanks in advance.
-
I know the standard advice is "enjoy your last summer before grad school" but I'm definitely going to be reviewing before classes start since I've been out of undergrad for two years and my school's economics major wasn't very rigorous. I've been working through a calculus book (Kline) to sharpen up basic skills, and was planning to do the same for linear algebra. I have Simon and Blume "Mathematics for Economists" that I bought at the recommendation of a professor and want to work through as well. Is this a good plan? Anyone have other recommendations?
-
I'm an idiot. I just notice the program 's website says: Applicants to the Ph.D. program should have completed the coursework listed above for entrance to the M.S. program. In addition, applicants should have completed: microeconomic theory at the M.S. level econometrics or mathematical statistics at the M.S. level multivariate calculus and linear algebra I double major in math and econ and have real analysis, linear algebra, math stats, probability, and all but they are not M.S. level courses. Should I not apply? The application is due like...tomorrow.
-
Beginning Math camp in a few weeks. I spent a few years out of school, so I'm rusty on my Calc1-3 and Linear Algebra, although I'm starting to recap it now. My fear is about Real Analysis. If I get through Calc and Linear Algebra, then I plan to self-study Analysis. What's the best way to balance everything? I've been told two different ways of proceeding: 1) Carry on with Calc and LA, and self-study relevant RA as I go through the PhD. I.e. designate 1/2 hours in the evenings during the PhD to focus on Math. Will I have enough time on top of the existing material to do this? 2) Someone said do this course now instead of refreshing Calc and LA (which I can use Math camp for). However, will this course be too much for me? Any advice would be really appreciated. Thanks! -
I'm trying to take UMD's PhD-level microeconomics as a think tank RA this fall. Last time I asked they told me my math background was insufficient (due to poor grades, I'm assuming) so I retook a bunch of classes. My old/new grades are below: My old grades from a top 30 undergrad w/ quarter system: Calc I-IV (A-. B+, B-, B), Linear Algebra (D, retook for C+), Advanced Linear Algebra (C-), Real Analysis I-II (B+, A), Intro to Probability Theory (B-), Intro to Math Stats I-II (C+, Pass) My new grades: Calc IV (A), Linear Algebra (A), Intro to Probability Theory (A). Retook Calc IV and Linear Algebra at my local community college; retook Intro to Probability Theory at UC Berkeley. Is there anything I'm missing here in terms of the math background needed to do PhD-level microeconomics? Is my B+ in Real Analysis I going to be a big deal here if I got an A in Real Analysis II? I realize the instructors still might decline to let me in on the basis of older grades, but I want to make sure I've done as much as possible to help my case.
-
Removed due to poor formatting.
-
I am a current undergrad at a top 5 (think HYPMS) university. I did not do so well in multivariate calculus and linear algebra (think B/B+), so I am thinking of taking a course at a UC this summer for remediation. Unfortunately, due to COVID, it seems everyone got the same idea, leaving it impossible to register for a course at UCLA/UCB. This leaves me with options at these schools: UCSC: Linear Algebra UCI: Multivariable UCR: Multivariable Linear Algebra I Was wondering if taking any of these courses would help remediate my ****** grade and at least show I am competent in these subjects. I do plan on taking harder courses next year at my school, and hopefully I'll do well. However, I was wondering if the quality of these schools should impact my decision in which school(s) I choose (I can choose multiple thanks to remote instruction), and which school I should choose.
-
Is real analysis really important for PhD admission? Is it possible to get into a top 50-70 program with only Calculus 1-3 and linear algebra? Thanks!
-
Hi All: I'm trying to see what math classes I'll be taking in my MA program from next summer, and was hoping somebody can point me in the right direction... Already planning to take: - Calculus IV - Intro to Linear Algebra - Intro to Advanced Mathematics - Elementary Probability & Statistics - Intro to Real Analysis - Topology - Combinatorial Mathematics I can take 2 more math classes (will do MA for 3 years to prepare well for RA and PhD)... could you please help me choose from the following? - Intro to Abstract Algebra - Linear Programming (is this redundant from Econometrics?) - Principles of Analysis (I and II for 2 semesters) - Complex Analysis (I see that others have taken this in the past) - Probability I have Economic Theory research interests so I would like to have an excellent mathematical preparation... thank you!
-
Hi, I didn’t do well in my undergraduate Linear Algebra II class and got a B- - mainly because I bombed my final exam. Anyways, I just graduated and am now working as an RA, and have the opportunity to take post-bacc classes at a local university (different form the university I attended). Should I retake Linear Algebra, or should I just leave it and take other classes like stochastic processes or the statistics version of Linear regressions? Any advice would be appreciated. Thanks! :)
-
Linear Algebra original grade: C Multivariable Calc original grade: P IB Math (calc): taken in high school (don't even recall my grade...A or B Just took "Linear Algebra and Real Analysis": A- Should I retake a standalone Linear Algebra course? Should I go back and take undergraduate Calc 2 & Differential Eqs? At this point is it sufficient to just retake Multivariable Calculus? Also- Micro theory: B+ Macro theory: C+ Should I retake Macro or Micro? These were both the 'more advanced' versions of micro and macro available to undergrads but this is not necessarily clear from the course names.
-
The math courses I hope to have finished by undergrad end are: - calculus sequence (single var, multi var, linear algebra/differential equations) - linear algebra - real analysis 1 and 2 - probability (calculus based) - statistical inference - mathematical statistics - stochastic processes - probability (measure theoretic) Is there an important math class that I'm neglecting? Are any of these functionally irrelevant for applications and should be replaced?
-
I am a final year economics undergrad with basic mathematics background (calculus sequence, linear algebra, differential equations, intro real analysis, econometrics). I have the opportunity to take a year of mathematics, involving a choice of upper undergrad mathematics classes such as general topology, lebesgue measure, numerical analysis, linear algebra 2, mathematical statistics, linear models, complex analysis, PDEs, stochastic processes, among others. In your opinion, should I take this year of mathematics or would it be better to begin postgraduate economics immediately? Any advice appreciated. edit: to clarify, I am in Europe, hence Masters before PhD
-
I'm currently an undergrad, and I have a quick question about taking grad linear algebra: Initially, I took a matrix theory/algebra class (which was called something like Matrix and Linear Transformations and so it covered some parts of linear transformations), and got a C initially, which I then retook and got a B. Later, I took a course that's actually called Linear Algebra (so this is the more legit linear algebra course & covers everything that was covered in matrix theory/algebra class + more linear algebra stuff & is mathematically rigorous, proof based), and got an A. I have an option to take grad linear algebra as an elective, and I was wondering what you guys think, given that even though I got an A in the Linear Algebra course, those bad grades in matrix algebra worry me. (I had some hard time with math in the beginning, but did better as I took harder courses: in fact, I got straight straight As the past three semesters in all math courses including: two sequences of Real Analysis, Topology, Stochastic Process, PDE and Fourier series, and so on.) I would like to be competitive for top schools (20 or higher), so let me know what your thoughts are, thanks for the help!
-
Is an Operations Research course the same as a Linear Programming course, at least at the undergraduate level? Some schools offer a course in operations research, others in linear programming, and I've seen some people use them interchangeably, so I was wondering. Thanks!
-
I have a couple of choices of linear algebra courses to take. - A is standard linear algebra course, uses Strang's Intro to Linear Algebra (should give context on the material) - B is computational linear algebra, ie it has a focus on computational applications, MATLAB programming, etc. It covers the same material as course A in a sense, but probably with less focus on the theory. - C is proof-based, abstract linear algebra, uses Linear Algebra Done Right as a textbook (for context on the material). Known to be the hardest of the three. B seems more helpful towards possible research work, as it provides experience with computational methods that could be useful in doing RA work (and also in applying to pre-doctoral RA positions, which I'm considering). C seems the most helpful for signalling, but I don't know how valuable linear algebra is as a signal compared to other math courses (I've heard it's not) and the potential grade hit/opportunity cost may not be worth it. A is probably the least work and maximizes probability of a good grade while giving me time to focus on other math courses. Which should I take?
-
Undegrad: Econ Major at NYU. 3.7 GPA. I wrote an undergraduate honor thesis. Probably not gonna be very helpful. Grad: Stats and Math at Columbia. Probably will finish with a 3.5, or 3.3. Math and Stats courses: Finished:Calc 1-3(A), Linear Algebra(A), Real Analysis 1&2(A-), ODE(B), Probability(B), Mathematical Statistics(B+), Linear Regression Models(A-), Statistical Computation(B+). Work-in-Progress: Stochastic Processes, General Linear Modeling, Machine Learning. Will take: Optimization, Topology, Measure Theory and Fourier Analysis (Yes, this is an actual course despite its makeup). Caveat: I read up all the FAQs about math prep for Econ PhD. Sources include NYU, Berkeley, Cornell. I am basically catering my math profile for these three schools. Econ Courses: Basic stuff that you need to graduate as an Econ major. No advanced stuff. GRE: The first time I took it I got 327. Will take it again and hopefully land at 335. SOP: Very general and explains my passion for using math tools to solve economic issues. LOR: One from my undergraduate honor thesis advisor. The rest comes from my math profs who taught me analysis. Research Experience: Only came from my undergraduate thesis, which was supervised. Target Schoos: Berkeley, NYU, Cornell, Brown, JHU. Reach Schools: Vanderbilt, Rice, BU&BC, Chapel Hill, Washington St Louis. Safe Schools: I'll eat up any school that is outside the top 30. Questions: 1. Am I on the right track here? That is, am I doing enough? 2. I am extremely stressed out because I think F2019 will be a tough app year for Econ PhD. Anyone can share their thoughts on that? 3. Idk. Just thoughts? Any?
-
So last semester I took linear algebra II and ended up getting a B-. Long story short, I did fairly well on my two midterms (A-) and quizzes, but due to the stress and pulling an all-nighter before the exam I did very badly on my final and was below average. After the final curve I somehow ended up at a B-. This grade is non-disputable and I am stuck with it. I was wondering how much this would impact my application. I now have a 3.8 gpa (down from a 3.87) due to this course. The grades in my other courses are as follows: Math Courses: Calc II (B- freshman year first semester), Calc III (A), Linear Algebra and Differential Equations (A+), Intro to Probability (A), Probability Thoery (A), Linear Algebra II (B-), Numerical Analysis (A-) Econ Courses: Intro to Econ (A), Intermediate Micro(A), Intermediate Macro(A), Econometrics (A), International Trade (A-), Senior Research Seminar (A-), Financial Economics (A), Intermediate Financial Theory (A+), Behavioral Economics (A+) I am taking Real Analysis, Concepts of Statistics and Applied Econometrics this semester. Assuming that I don't mess up again and obtain A's in all of them, would the B- in Linear Algebra II still have a large negative impact on my application (keep me out of getting into anything Top10)? I will be working a 2-year full-time RA job at a Top 10 university and will be applying Fall 2019. Any help or advice is much appreciated. Thanks!
-
Undergraduate Econ degree from top 10 bad gpa 3.1 high iq - think 180 This is my plan bachelor in math ma in financial economics basically all the necessary prerequisites: grad level micro/macro/econometrics, multivariable cal, linear algebra 1-2, diff equat, ode, topology, prob stats(multi calculus) Who out there got into the ivy leagues?
-
Hi I will apply phd next year and need some advice for my course selection. Basically, I am facing two paths, 1. Take econ elective course which require me to write a master thesis. I expect to be able to build good relationship with the professor and get a good LOR from him. 2. Take stochasic process and machine learning course. FYI, I majored math in undergrad and courses I have are cal1, 2, 3, linear algebra, differential equation, analysis, real analysis, probability, intro stats, theoretical stats, non linear dynamics, abstact algebra, numerial analysis. (Mostly A/A- but B+ in diffequ and B in cal I) Under this circumstances, should I need to take machine and stochastic analysis? I am aiming TOP 5-10.
