Undergrad Institution: Top 50 in the US (known for math and stats)
Major: applied math and stats GPA: 3.97
Type of Student: Domestic male GRE General Test: Haven't taken yet, but I'm expecting 168+ in Q and 155-160 in V.
Programs Applying: Statistics PhD
Research Experience: Nothing impressive... but I've worked in a research-type role for several years after undergrad.
Letters of Recommendation: One of my college professors and two advisors/mentors from work. My advisor has a PhD in a quantitative field and will be able to talk about my research potentials.
Programming Skills: Python and SAS
Relevant Courses: all undergrad-level --- calc I-III, linear algebra, differential equations, abstract algebra, mathematical stats, probability theory (calc-based), stochastic processes, applied regression, and several more applied stats courses. I'm concerned that I have not taken analysis, but calc III, linear algebra, and differential equations were specifically for advanced math students and required us to learn how to do proofs (in addition to abstract algebra and stochastic processes, which were also proof-heavy).
Schools: Duke, Washington, Columbia, UNC, Michigan, Wisconsin, Penn State, Purdue, UCLA
My main concern is: Is my math background enough to get into these programs? Another possible path I can take is do a masters in math (or stats?) instead to build a stronger math foundation, but I wasn't sure if that's worth it if my ultimate goal is PhD. Thanks!