babystatistican Posted July 1, 2019 Posted July 1, 2019 (edited) Hi, I am a senior who is applying to Stats Ph.D. programs in the upcoming fall. Here are my stats. Ethnicity: Southeast Asian Female (International) Undergrad Institution: San Francisco State University Major: Statistics GPA for upper-division and major classes- in 3.9 range Math classes Calc III (A), Prob and Stats I(A-), Prob and Stats II (A), Python Programming (A), Intro to Proof (A), Intro to SAS (A), Linear Algebra(A) Will take ODE, Game Theory, Linear Modeling, Design and Analysis of Experiment, Probability Models in Fall 19, and Real Analysis, Categorical Data Analysis, Data Mining in Spring 20. Research Experience: Currently working as a student research leader in a summer program, had a lower level research Work Experience: TA, Tutor, Grader, Research Leader GRE general: will take it in September. Schools Applying for PHD: UC Berkely, UC Santa Barbara, UC Riverside, UC Santa Cruz, University of Michigan Edited July 1, 2019 by babystatistican
Stat Assistant Professor Posted July 2, 2019 Posted July 2, 2019 Berkeley and UMich may be difficult to crack, especially since you are an international student (there is much more competition). If you want to try a "reach" school, I would recommend NCSU or UWisc. The others on your list seem reasonable targets, provided that you do well in Real Analysis. I would add more schools ranked at or below the level of UCLA to your list.
Geococcyx Posted July 2, 2019 Posted July 2, 2019 Maybe it's not a big deal, since Stat PhD didn't mention it, but could you potentially take Real Analysis in the fall instead of the spring? I'm not sure it would do much, but that way if programs were on the fence about you, they could ask you to send your fall grades and look for a high Real Analysis grade to convince them. That also works for programs with application deadlines in January or later (Texas A&M and UConn are two places that come to mind), plus Wisconsin asked everyone for their fall grades this last cycle from what we could tell.
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