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marmle

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About marmle

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    Espresso Shot

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  • Gender
  • Application Season
    2017 Fall
  • Program
    Statistics/Biostatistics

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  1. In order to roughly give you an idea of where you're competitive, you'd need to provide a profile. However this won't be of much help as you've only completed your freshman year (and since you said it was rough I'm guessing your grades weren't the highest). From looking at the schools you want to apply to in the future, it looks like you're applying mostly based on brand name/undergrad prestige, and not based on research interests. Those schools are usually arbitrarily more competitive because of people just applying to them for their name. In terms of what safety and match schools are, they're not very well defined for phd programs, as admissions can be a crapshoot (unless you have an amazing profile). Usually "safety"/"match" schools are those that accept a large number of students (mostly large state school programs)/ some of the lower ranked schools, and "reach" schools are schools that accept a smaller number of students (brand name schools)/higher ranked schools. My advice would be to forget about choosing which schools you're applying to until the spring/summer before your senior year. You'll probably have a better idea of your research interests, and your profile will be a good indication at that point of where you should apply.
  2. I don't think any schools will fly you out pre-admisison unless they do on site interviews (e.g. Duke stats, a few biostats schools). However, most schools will pay to fly you out if you're admitted (all of the programs I was accepted to offered to fly me out). There might be a few exceptions (maybe some schools don't have as much funding for recruitment as others), but I would definitely not try to purchase any flights till you're accepted/the schools tell you about their accepted students days. If you're worried about being able to buy the flights before being reimbursed, some schools can book your flights through their travel agencies.
  3. No, an A- won't hurt your chance for a masters program (or PhD program) given A's in all of your other math classes
  4. Undergrad Institution: Top 35 US Undergrad Major(s): Math, Computer Science Minor(s): GPA: 3.94 Type of Student: Domestic white male GRE Revised General Test: Q: 167 (93%) V: 163 (92%) W: 4.0 (59%) GRE Subject Test in Mathematics: M: Didn't take Programs Applying: Statistics/Biostatistics PhD Research Experience: One summer of SIBS, one REU in biostatistics Awards/Honors/Recognitions: Pi Mu Epsilon, Awards for being in top 5% of class Pertinent Activities or Jobs: Math Grader, Computer Science TA since sophomore year Letters of Recommendation: Should've been good Any Miscellaneous Points that Might Help: Nothing that really sticks out Applying to Where: Berkeley - Statistics Reject 3/7 Chicago - Statistics Accepted 1/24 Washington - Statistics Waitlisted 1/18 CMU - Statistics, Joint Statistics+ML Reject 2/23 Duke - Statistics Reject 2/3 Wisconsin - Statistics Accepted 2/24 Michigan - Statistics Reject 3/14 Columbia - Statistics Reject 3/8 Cornell - Statistics Reject 4/13 Yale - Statistics Interview request 1/27, Reject 2/21 UT-Austin - Statistics Reject 3/21 Washington - Biostatistics Accepted 1/6 Harvard - Biostatistics Interview invitation 1/6, Waitlisted 2/3 UNC-Chapel Hill - Biostatistics Accepted 1/3 Penn - Biostatistics Interview invitation 12/20, Accepted 2/15 Princeton - Operations Research Reject 2/10 Chicago - Computer Science Accepted 2/23 If anyone wants to see more details about my background, look back through my posts. Overall very happy with my acceptances. Also it's of note that I didn't take the math gre and got into one program that recommends it (Chicago) and got waitlisted at another that recommends it (Washington), so the advice on this forum from the past that you don't need to submit a math gre to get into programs that recommend it seems to be true.
  5. You have a >3.7 gpa from one of the best schools in the country (that's known for grade deflation), a perfect gre quant score, 80th percentile on the math gre (Stanford's listed average is probably skewed by internationals so your score is probably above average for domestic students), two summers of REUs and additional research, and you've taken graduate classes. I'm not sure if you're judging yourself as not having an amazing profile because you're comparing yourself to other math majors who're applying to math phd programs, but for statistics your profile is about as good as it gets! And you probably would've fared well applying to math phd programs too from the looks of it. I don't have any real input since both programs are great and there really isn't a wrong choice for you. If there's nothing related to specific research interests that draws you more to one school than the other, my suggestion would be to choose the program you think you'd be happier at socially/ outside of the classroom (e.g. do you like berkeley or palo alto more, is the stipend significantly better at one school, were the other perspective students at one school more fun to be around, etc).
  6. I don't know if I'd suggest Elements to someone who's just trying to self study some stats before a graduate program, especially if they weren't specifically interested in machine learning
  7. The standard undergrad math stats books are Wackerly, Rice, and Larsen and Marx. You only really need to self study from one. If you want to preview what you'd most likely see in grad school, Casella and Berger is the standard for the first year of a grad program. For Bayesian stats the standard is Bayesian Data Analysis (BDA) (Hoff also seems like another pretty standard bayesian stats book). None of these require real analysis (but it'd help to have some analysis).
  8. Did anyone see the posting in the results search saying Columbia stats already sent out phd offers? Anyone know if it's true?
  9. What's your mathematical background like?
  10. Not saying it's irrelevant but that you have to take into account placements since that time. Just as an example it seems like Hopkins has had a ton of placements since 2011-2012ish (http://www.biostat.jhsph.edu/people/alumni/alumlist.shtml). The problem is as you said there's no consolidated data and we're all pretty much just showing anecdotal evidence, and we probably notice/remember some things more than others (e.g. you see Michigan placements, I see Hopkins placements). In reality going to any of these programs is most likely going to set you up well, and as you said, advisor matters more than the overall program! Not trying to start a fight or diss anyone either haha
  11. While I agree that all of the schools in question are great and you can have good placements going to any of them (and the gap between programs probably isn't as big as it seems), you have to acknowledge that biostat_prof's statements are gonna be somewhat biased considering it seems as though they're faculty at UNC (also that thread is 4 years old!). Also what @Innominate was saying, where's the data. And also you need to think about criterion for what saying one school is better than the rest at academic placement means (e.g. how recent are the hires, are the placements at some of the top programs or some of the lower programs (or even unknown programs), do postdocs count?, how do you compare biostat department placements to stats department placements or placements in other related departments, etc.)
  12. Yeah idk about this. There's a reason why Harvard/UW are considered in their own tier in biostats followed by JHU/UM/UNC
  13. I think since you seem to have a good idea of what you want to do, the overall placements of the program aren't important so much as the placements of the professors you're interested in. Hypothetically, if someone from UM stats was placed at like Stanford or Berkeley but their research area/advisor were in something like spatial statistics, that shouldn't really affect your decision. You seem to have POI at both schools, so look at where their students have published/ been placed.
  14. Eh, I wouldn't really draw conclusions from those few data points (yale and brown biostats are fairly small programs). Also if you look at Penn biostats academic placements specifically, they're not amazing, only have one recent placement at CMU (from a guy who worked with Dylan Small). UW has placements pretty much everywhere.
  15. You can't really go wrong with either 2nd semester linear or measure theory (there's probably not diminishing returns if you're doing well in all of these analysis classes). I don't know which an admissions committee would look more favorably at (maybe measure theory?), but I'd try to take both if you can. The stochastic models models class sounds interesting but it might be something you'd end up taking again in grad school (so maybe sit in on it, take it pass/fail, etc).