interlockjohn

Thanks for your reply SAP. Davis does have an internal transfer I could look into, but it wasn't high on my list due to Davis being in a college town. It seems like I can't be too picky, even if I do well in the master's program, which is slightly disheartening. I think I'll apply to a majority of the UC's as reaches, and consider a few of the 37-80 schools you mentioned for targets. My goal is industry afterwards so the ranking may not matter as much, but I'd still like to go somewhere my research interests are prevalent.

Hello everyone, I am upcoming MS Stat student at UC Davis, and I'm interested in continuing on into a PhD program after I finish my MS. I'm not sure if I would be competitive for those schools I mentioned below. I'd appreciate it if I could get an approximate range of schools I should be looking at. An additional note, the program at Davis does not offer a thesis, but I think I should be able to do some research with professors and possibly get a paper out. The question is, what can I do at my MS program to best improve my chances for a PhD admissions (2023 entrance)? I'm assuming I should try to take some more proof based math courses as well as ace my MS degree. Would this put me in a decent spot for admissions, or are there additional things I need to be looking at? My profile is as follows: Undergrad Institution: CSULB Major(s): Math, Emphasis on Statistics GPA: 3.6 cum laude Grad Institution: UC Davis Major: Statistics GPA: Tentative Type of Student: Asian/Domestic GRE General Test: 168Q, 165V GRE Subject Test in Mathematics: Not taken, not sure if I should Programs Applying: Statistics PhD Research Experience: None Awards/Honors/Recognitions: Dean's List for a majority of semesters Pertinent Activities or Jobs: Stats and Math Tutor for 2 years Undergrad Math/Statistics Grades: Calc I (A) , Calc II (A), Calc III (B), Intro to Probability (B), Mathematical Statistics (A), Applied Regression (B), Linear Algebra (non proof based) (A), Abstract Algebra (B), Graduate Statistical Inference (B), Multivariate Statistical Analysis (A), Numerical Analysis (B), Machine Learning (A), Real Analysis I (B), Discrete Math (CR, COVID grading policy) Courses I plan to take: I'm hoping to take a full sequence of real analysis during my MS, a mathematical stat sequence, and mainly graduate level stat electives (would love pointers on which one would be most beneficial) Research/Career Interests: Machine Learning, Statistical Learning, Graph/Network Theory, Inference Schools Currently Interested In: UCDavis, UCIrvine, UCLA, UCBerkley, Columbia, Yale, UTAustin Thank you in advance!

Undergrad Institution: CSULB Major(s): Math, Emphasis on Statistics GPA: 3.6-3.7 Type of Student: Asian/Domestic GRE General Test: Not taken yet GRE Subject Test in Mathematics: Not taken, not sure if I should Programs Applying: Statistics, maybe CS Research Experience: None Awards/Honors/Recognitions: Dean's List for a majority of semesters Pertinent Activities or Jobs: Stats and Math Tutor for 2 years Letters of Recommendation: 1 Stat undergrad advisor, 2 Stat graduate advisors, all good, but not amazing. Math/Statistics Grades: Calc I (A) , Calc II (A), Calc III (B), Intro to Probability (B), Mathematical Statistics (A), Applied Regression (B), Linear Algebra (A), Abstract Algebra (B), Graduate Statistical Inference (A), Multivariate Statistical Analysis (A), Numerical Analysis (A), Machine Learning ( W, but retaking next spring), Real Analysis (W, retaking in Fall 2021), Discrete Math (A) Courses I plan to take (during admission's process/Fall2021): Graduate Linear Regression, Real Analysis, Random Processes Research/Career Interests: Machine Learning, Bayesian Statistics, Data Science at a Tech Company Schools Applying to (prefer to stay in Socal, unless the program lines up with interests): MS: UCLA (Master's of Applied Statistics), Duke (Statistical Science: Data Science track), UCB, USC PhD: UCI, UCSB I'm still very torn about whether or not I want to do a PhD. I know generally, it isn't great to do a PhD if you're not dead set on it, but I would like to work in a field of data science/machine learning that is a bit more research intensive, as in I don't want to be a code monkey. However, I'm not sure I am capable of handling math intensive courses, mental health wise. I feel like my grades aren't that impressive compared to most students here, but I'm sure some students here can relate that getting these grades takes a toll on your mental heath for a while, and at times I feel like I can't cope with it, despite still managing to pull out a decent grade in the end. Despite this, I still want to consider the PhD because although I may not have the immediate smarts for it, I think my perseverance can make up for a bit of it. Or maybe I need a reality check haha... Another problem is I'm not sure what kind of research I would even want to pursue in a PhD. I've enjoyed the graduate stats course I've taken and the graduate advisers I've talked to about for research, but the actual content and material wise, I'm not sure what that entails since my undergrad institution has little to no research for statistics and I was not able to secure an REU for the last 2 years. Both of these factors really make me rethink my decision if even a PhD is right for me, but I would rather know now that lead myself blindly into one. The main driving factor that even made me consider doing the PhD in the first place is job prospects and the slight thought that MAYBE I am cut out for one, academically. Ideally, I think doing a masters is my best bet, but I just wanted to read people's opinion on a PhD. This was pretty open ended, but I'd like some advice on my whole PhD shpeal, as well as what type of programs I should be aiming for given my profile and interests. Thank you much in advance and stay safe! J