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There's a nice thread in this forum that covers topics worth reviewing before starting up a grad program in statistics, but I wasn't able to find any threads providing recommendations on how to prepare for 2nd-year Stat PhD coursework, which I understand tends to a big jump from 1st-year coursework/Casella & Berger in terms of required mathematical maturity. Does anyone have recommendations for texts, self-study strategies, or other resources that provided good preparation for their 2nd-year PhD coursework? In my program, the 2nd-year probability/measure theory course has a reputation for being particularly challenging, so recommendations for gaining exposure/an introduction to measure theory would be particularly welcome to this 1st-year student.

@BrownianEmotion pm'd you!

Chiming in a bit late here, but as a former history undergrad (now 6 years out) who started an MS program with funding this fall: My math background was probably a little lighter than yours--besides Calc I-III and linear algebra, I took the intro probability/math stat sequence, a proof-based linear algebra course, and a number of undergrad-level applied stat courses before applying to MS programs only. I got into most of the schools I applied to, and with funding from ~half of them (I applied to Davis but was rejected; I ended up accepting at a similarly-ranked school). Since you have taken analysis, I don't think you're necessarily reaching too high to apply to PhD programs. If you haven't done so already, it couldn't hurt emailing stat grad chairs at the schools you're interested in to probe this further, though the timing probably means you won't hear back from anyone right away.

I'm a bit of a nontraditional applicant to MS statistics programs exclusively--I was a history major at a small, liberal arts college and my quantitative courses consisted of one intro stat and one intro comp sci class. A couple years ago I took a free online Calc I class for fun (thanks Coursera) and subsequently took Calc II/III and Matrix Algebra at night through a local community college. In September 2015 I took a leap and became a full-time student at a public state university after a few years in the workforce, taking Probability Theory, an intro Math Proofs course, a Design of Experiments stats course, and a Stat Comp/Data Analysis stat course. This semester I'm taking a Math Stat course, an upper-level Linear Algebra course, a Regression/Time Series stat course, and a Java programming course. The ideal goal is to secure some degree of funding for an MS program (which explains some of my school choices below), but considering my circumstances I'd honestly be happy to get in anywhere. Undergrad Institution: Top 20 Liberal Arts College Major(s): History Minor(s): GPA: 3.56 Type of Student: Male, Domestic, Biracial (Caucasian/Taiwanese) GRE General Test: Q: 163 (86%) V: 165 (95%) W: 5.0 (92%) GRE Subject Test in Mathematics: M: N/A TOEFL Score: N/A Grad Institution: N/A Concentration: N/A GPA: N/A Programs Applying: MS Stat Research Experience: None. Awards/Honors/Recognitions: Dean's List one semester, decent-sized scholarship for undergrad. Pertinent Activities or Jobs: Digital marketing specialist at an academic research hospital. Letters of Recommendation: One from a community college math professor, one from an undergraduate stats professor with a decent number of publications in high-dimension reduction research, one from my former work supervisor. Any Miscellaneous Points that Might Help: Nontraditional background as noted above. Took a full year of math/stat courses between Fall 2015 and Spring 2016 to satisfy prereqs for most of the schools I applied to. Applied to: Ohio State - Admitted (1/21) California - Davis - Pending Vermont - Pending Temple - Pending British Columbia - Pending Oregon State - Pending

Thanks for the feedback! Much appreciated. Spoke with another forum member here and it looks like I should be able to take calc-based probability and mathematical statistics through Penn State's online program, so I'll plan on tackling those as soon as I'm finished with Calc III. Not my first choice to take these courses online, but there unfortunately aren't any cost-effective night-time options in my area.

I think I fall pretty squarely into the nontraditional applicant category. School: BA, top 25 liberal arts college (graduated 2010) Major: History GRE: V 165, Q 163, AW 5 GPA: 3.54 I took no true math/stats courses while an undergrad. A shame, looking back. I'm now working the the calc sequence and linear algebra at a local community college. Relevant Coursework: Tested out of Calc I after taking a MOOC Calc II: A Linear Algebra: taking this now--expecting to receive an A I'm planning on taking Calc III in Spring 2015. Based on what I've read in other posts throughout this thread, I'm assuming it makes good sense to also take the first one/two calc-based stats/probability courses in the general sequence in order to have a real shot with my applications, right? A bit of background: I currently work in digital marketing for an academic health system. I took the GRE in Fall 2012, and rekindled an interest in math while studying for that exam, which led to taking the MOOC referenced above. I've been interested in tacking toward a more quantitatively-focused career path, and this interest, along with my exposure to health research and work with physician-researchers, has led me to the idea of pursuing a MS/MA program in statistics in order to facilitate this professional move. I'd not averse to biostatistics programs, but I don't think I want to rule out statistics, either. Is it worth retaking the GRE to boost my quant score? Given my background, does it also make sense to assume I should save my money and not bother applying to top-tier programs? Any thoughts/suggestions/advice would be welcome and greatly appreciated.