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About MynahK

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  1. I was attempting to make the thread as broadly applicable as possible. That's where the unusual title comes from. ...Perhaps the level of generality I was originally aiming for with this thread is unrealistic. I am applying to computationally-oriented programs in cognitive neuroscience and psychology.
  2. The present structure of my SOP, described at a general level, is presented in order below. The numbered parts do not necessarily represent breaks in paragraphs - instead, they simply represent topics covered. I have not seen any other SOPs structured in this way, so I am hoping to hear others' thoughts on this particular structure, and on SOP structure in general. My current structure: 1st: Describe ultimate/overarching research goals (my 'big question', followed by a somewhat narrower sub-question). This brief section of the SOP resembles the sorts of 'research statements' that grad
  3. Note: In considering the comment below, keep in mind that my goals have changed since the first post in this thread. I am interested in data science, machine learning, and computational statistics, and I plan to pursue a Masters-level degree. In keeping with the general idea that courses matter much more than 'major/minor' titles, I am considering dropping my minor in Mathematics so that I am less constrained in my course options during my last year as an undergraduate (note that probability and statistics are taught separately from mathematics at my school). If I do this, I will have a c
  4. I am about to enter my senior year at the University of Pittsburgh as a Psychology Major and Math minor in the school of "Arts & Sciences" (the university's main liberal arts school). I plan to apply to both quantitative/'computational statistics'/modeling-oriented Cognitive Science PhD programs, and Statistics MS programs. I have been trying to explore my interests as much as possible within the constraints of my Arts & Sciences major and minor, but it is becoming increasingly difficult to do so. For example: during my final two semesters, I would like to be able to fit in some c
  5. I am planning to apply to 3-4 PhD programs in a sub-field of a science (which I'll call Z) that makes heavy use of computational statistics. At the same time, I will be applying to 2-3 quantitative masters programs in computational statistics and closely related areas. I suppose this situation is analogous to: 1) a Physics student applying to both Physics PhD programs and Applied Math or Computer Science masters programs 2) an Economics student applying to both Economics PhD programs and Statistics or Finance masters programs I've been working in a research lab in the science Z, and
  6. Thanks for your response, Noco7. I should probably add that upon further reflection, I'm not so sure that a career in academia is my goal. My interests are mainly in applied/computational statistics (especially as applied to 'life sciences') and experimental design. I'm currently leaning toward applying to masters programs in Biostatistics, rather than applying to PhD programs... with the goal of ultimately finding work in 'industry'. Any thoughts on taking ODEs vs upper-division Linear Algebra given the courses I've already taken? This question is not solely a "what might help my applicat
  7. Next semester, I have the option to take either Ordinary Differential Equations or upper-division Linear Algebra (I've previously taken "engineering, non-proof-based Matrices and Linear Algebra" and "Numerical Algorithms for Linear Algebra"). Given that this will be my second-to-last semester of undergrad, and I don't have much flexibility in my schedule otherwise, do you think future-me would thank past-me for having taken a theory-oriented course in Linear Algebra instead of ODEs?
  8. Previous math courses: - Calculus I-III - Linear Algebra - Numerical Analysis: Linear Algebra - A 'proof course' (prerequisite for Real Analysis) I've also taken basic mathematics courses required of Computer Science students. JZappa, thanks for this advice - I likely won't get the chance to take a (formal) course in Measure Theory before graduation, but I do plan to take Real Analysis (...though perhaps due to scheduling difficulties, I might only be able to take 1 semester before graduating). Thus, I will not quite match the 'ideal sub-ideal' situation you've described. One poss
  9. I am currently in my Junior year (2 remaining semesters), majoring in Cognitive Psychology and minoring in Mathematics. As I've become increasingly engaged in cognitive research and computational/probabilistic modeling over the past year, I've developed a strong interest in statistics and probability. My interests range from the study of stochastic processes and statistical algorithms to issues in research methodology and experimental design. My interest in statistics has also developed by reading online writings by statisticians such as Andrew Gelman and Cosma Shalizi, and reading methodologi
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