blueberry-pi

Thanks! Some really good points brought up above - agree UCSB is a bit of an outlier on the list, was included mostly due to personal preference around location. I heard UW and Michigan had relatively more onerous coursework/quals frameworks (for example, Michigan has 3 probability course requirements), is that true to the best of your knowledge compared to the other programs on the list? Having been in industry for a few years I prefer programs with lighter and more applied coursework/qual requirements. On a separate note for Duke, I originally decided to eliminate it given personal location preference, although location would not be an issue for either UW or Michigan. I understand there are a lot of factors involved, although was curious if you have any thoughts on what application outcomes for this list might look like given my profile? Again, I'm sure there'll be a lot of variance in decision outcomes from year to year, although it'd be helpful to know for example whether these kind of programs are realistic.

Applying for PhD in statistics/biostatistics after working in industry for a few years as a Data Scientist - would appreciate any thoughts, feedback, or advice on programs below given profile/research interests. Undergrad Institution: US Top-5 in Statistics Majors: Statistics, Applied Math GPA: 3.91 Type of Student: International Male Math Courses (All A's): Real Analysis, Complex Analysis, Linear Algebra 1/2, Abstract Algebra, Numerical Analysis, Differential Equations, Calculus 1/2/3, Discrete Math Statistics Courses (All A's): Stochastic Processes, Time Series, Experimental Design, Linear Modelling, Data Science 1/2, Probability Theory, Statistical Computation Computer Science (All A's): Algorithms, Machine Learning, Deep Learning, Databases GRE: 168 Q | 163 V | 5.5 W Research Experience: 2 years in applied statistics (3rd author publication in lower-tier journal - did most of the coding), 1 year in sociology (no publications - mostly database management) Work Experience: 3 years as Data Scientist at large tech company Recommendation Letters: 2 from research advisors (strong letters), 1 from professor with multiple classes and strong performance (mediocre letter) Coding Experience: Python (expert), R (experienced) Research Interests: Causal inference, applications to social sciences (specifically education/public policy), applications to public health policy Programs Considering: UC Berkeley Stats PhD Harvard Stats PhD CMU Stats PhD UCLA Stats PhD UC Santa Barbara Stats PhD Harvard Biostats PhD Penn Biostats PhD Brown Biostats PhD MIT Social & Engineering Systems PhD NYU Data Science PhD Are there programs here which don't sound like a great fit with my interests and profile, or any not here which could be a fit? I recognize my list is a top-heavy, but I'm satisfied at my current industry job and would go back to school only for a relatively well-regarded program, with the end goal of tenure-track professor at a R1.