cyberwulf

"Mathematical culture course" = "course where you'll be exposed to more mathematical ideas, which is generally a good thing if you're going to be studying statistics."

Stochastic might expose you to a few more topics you'll cover in grad school, but I would view both as "mathematical culture" courses, to take if you find them interesting.

Yep, 100% agree with Safferz. In general, I think prospective students *way* overestimate the importance of having someone "famous" write them a letter. Sure, it's nicer to have a great letter from a well-known prof than an unknown one, but if there will be a significant difference in the enthusiasm of the letter, you should go with the stronger letter regardless of the reputation of the letter writer.

Huh! I didn't know that IA State offered on online MS. If the institution is reputable (and Iowa State is), I see no reason why an adcom would treat it any differently than an "in-person" degree.

Don't do it. There are about 40 departments of stats or biostats which top biostat PhD programs view with respect, and none of them is online. You should do your best to get into a solid stats or biostats M.S. program (the top 40 in the US News rankings of Stat/Biostat programs isn't a bad place to start).

The list of Biostat M.S. programs where good performance will help you get into a top-notch PhD program is, unfortunately, pretty short. The list of well-respected stat M.S. programs is a little bit longer, so you might want to think about that as a possible route (eg. consider Michigan State stat as a backup). I would strongly counsel you against any stat/biostat program that's much outside the top 40 on the U.S. News rankings. Excellent performance in more recent, upper-level courses will certainly serve you well. Job experience isn't really relevant; but, by the same token, tutoring and volunteer experience probably won't make much of an impact on an adcom either. The 3 key elements of applications are grades, GRE scores, and letters. Good luck!

I think you'll be borderline for an M.S. at Michigan; unfortunately, I don't think your record's quite good enough to get into their PhD (which is top 5 in the country). An M.S. from Grand Valley State likely won't help you much; performing well in a weak program really won't show UMich that you have what it takes to hack their PhD program. Assuming you have a bit of geographical flexibility, consider applying to a few other Big 10 M.S. programs. Specifically, you could look into Minnesota, Iowa, and Ohio State. Good performance in an M.S. at one of these places would be an asset on your future applications to PhD programs. Oh, and Minnesota has some MS admissions stats on their website -- I suspect Michigan's numbers would be pretty comparable: What are the average GPAs and GRE scores of students admitted to the MS program? Median GPA: 3.64 Median GRE scores: 770 Quantitative, 560 Verbal, 4.0 Analytical Writing

If something is "strongly recommended", chances are you won't get in without it unless there are exceptional circumstances.

It doesn't matter. These are both pretty far removed from what you will need/see in classes at even the top stat programs. Yes, it's good to know what "i" is, but only the most theoretical statisticians (who should more properly be called probabilists) have more than a passing familiarity with complex variables. I might even lean towards the graph theory course: one current "hot" area of statistics is social network analysis, which might use some of the concepts you'd be introduced to in that class. Bottom line: Take what you find most interesting!

That TOEFL score might be your biggest problem. Places with a minimum of 100 won't even consider your application -- you might want to make sure that none of the places you're applying have a minimum > 97.

I suppose it depends on your definition of "superstar". But I guess what I mean is that if you: 1) Went to an undergrad school with a decent reputation (say top 100 in US) 2) Graduated in the top 20% of your major (not necessarily math) 3) Have the math prerequisites 4) Got a GRE quant score > 85th percentile 5) Have positive letters that say something interesting about you Then you will at least be in the discussion for admission at the top biostat programs, and many good stat ones (the top stat ones might have a slightly higher bar for math background/performance). In other words, you don't need to be: 1) The top math student in your cohort (that girl/guy's probably going to a Math PhD program)... nor even a math/stat major 2) A graduate of an Ivy League or elite liberal arts college 3) Published 4) The best student any of your professors has ever seen/worked with (well, unless you're coming from a school nobody's ever heard of) So, I stand by my "don't have to be a superstar" assertion. Of course there are a lot of good students in the field, but they are not (warning: math/semantics joke) uniformly exceptional.

At least in biostats, nobody expects prospective students to have established any relationship with a faculty member before applying; in stats it should be pretty much the same deal. You might be lucky and get a faculty member excited enough to "talk up" your application to the admissions committee, but you also run the risk of annoying people, which certainly wouldn't work in your favor.

I'd wager you have a good shot at being admitted to most of the places you listed, though opinions on this may differ around here. Most PhD programs offer full funding to their students, so if you get in you shouldn't have to worry about money (at least to the extent that you can manage to eat/live on a typical grad student stipend). MS programs are a mixed bag; some offer funding to many students, others to a few, and still others to none.

This certainly wasn't my indented message. However, the OP did acknowledge a few potential weaknesses in her/his application, and an adcom at a top-5 program might prefer a student with a 3.7 with glowing letters and a track record of success in challenging (i.e. "honors") courses. But I have noticed that opinions here do tend towards the very pessimistic when people inquire about their chances for admission to stat/biostat programs. The reality is that, at least in comparison to other fields like math/physics/CS, the student talent pool in statistics and biostatistics remains quite shallow, and you don't have to be a superstar to be admitted to even the best programs.

(I'll use the old GRE scores here, because we don't know much about the new ones yet) Quant: At good programs, a large proportion of applicants score 800, so you can really only hurt yourself if you are far below that level. Anything below 700 is probably a non-starter for a decent PhD program. Verbal: Mostly irrelevant, but if your verbal score is really exceptional (700+), that can be an eye-catcher. Analytical Writing: Same as verbal. Most applicants score 3.0-4.5, below 3.0 could be trouble and 5.5-6 might be viewed as something in your favor.

I think this is a little too pessimistic. With the record as stated (plus the math courses currently being taken, assuming they are accredited and you do well), I suspect you would be borderline for a stats PhD program in the 10-20 range. And you would likely be a solid MS admit at most programs. But, as suggested above, even though you might get into a PhD program somewhere, you may want to do an MS first to see whether graduate study in stats is for you.

Strongly concur with most of what Poisson said. If you're considering biostats, I suspect you would be competitive for all the top programs (Harvard, Hopkins, Washington, Michigan, Minnesota, UNC, etc.) given your strong quantitative background. If you're interested in the biological applications of statistics, you might be better off at a top-tier biostats department than in a second-tier stats program. Also, a biostats degree can lead to a plethora of non-academic research positions. When I was applying to graduate school, I applied to both stat and biostat departments. I ended up in biostat, and have never once regretted the decision. sisyphus, feel free to PM me if you have more questions.