humber

Thanks Bayesian1701 and bayessays - you've certainly given me a lot to think about!

I'm not really in a hurry to graduate - just something that I thought about when I realized I could hypothetically graduate next year. Thanks for the suggestion! I think if anything it could be a good learning experience going through the whole application process, but I don't know if I'd just be throwing away time/money at a unrealistic chance.

Going into my 3rd year and I've been thinking about graduating a year early (i.e., in 2019). Should I even consider graduating early and applying to PhD programs with the following profile? Undergrad Institution: US Top-5 in Statistics Major: Statistics GPA: 3.95 Major GPA: 4.0 Type of Student: Asian Canadian Male Courses: Real Analysis (A), Probability Theory (A+), Statistics Theory (A+), Linear Algebra 1-2 (A+, A), Data Computing (A+), Discrete Math (A+), Calculus 1-3 (all A+), Data Science (A) Courses for Next Year: Real Analysis II, Stochastic Processes, Abstract Algebra, Machine Learning, Numerical Analysis, Linear Modelling GRE: Q: 169 V: 165 W: 5.5 Program Applying: Statistics PhD Research Experience: 1.5 years in psychology lab helping with database management and surveys (no publications). 1 semester in a independent reading project in pure math. Recommendation Letter: 1 from research advisor, 2 from professors/lecturers I've had. I don't expect any to be particularly strong. Coding Experience: R, Python Programs Considering: Michigan Wisconsin Toronto UCLA UC Irvine UT Austin Michigan State UC Santa Barabara I've done well with the courses I've taken so far, but I've only really completed the bare requirements and I'm not sure if I should even consider applying for 2019. If I were to apply for 2020, I'd have actual grades for the courses I'm planning on taking next year instead of just "In Progress," a second major (math), and likely stronger recommendation letters. Any thoughts, comments, or advice would be much appreciated!