cyberwulf

The logic behind dividing by the standard deviation of the scores on a test (or the sections thereof) is that getting a high grade is less "meaningful"/"impressive" if there is a lot of variability in the scores than if there is little variability. For example, consider the following sections of a test: In Section 1, Student X scores a 90%. On this section, half the students scored 90%, and half the students got 50%. In Section 2, Student X scores a 90%. On this section, all the students (except Student X) got 70%. In both cases, the average section score is ~70%, but it could be argued that Student X's performance on Section 2 is more "remarkable" and should therefore be rewarded more than their performance on Section 1. Dividing scores by the standard deviations (larger in Section 1, smaller in Section 2) is one way of accomplishing this.

1. You're applying to Masters programs, which are typically moneymaking programs for schools. They will take anyone they feel can get through the program. 2. Difference between a 169Q and 166Q is meaningless; it's well within the "test-retest" margin of error. 3. What constitutes a competitive GPA depends strongly on your school and the courses you took. A 3.66 from a top 50 university is a fairly strong record; in fact, I think you would be competitive for PhD admission at most of the places you applied.

Brown is solid, and good performance in a Masters program there will be respected by PhD adcoms.

Don't worry, you'll be fine. I wouldn't be surprised if you got into all the places you applied.

Usually, an interview is followed by an admissions offer, but I don't know the exact processes of all departments.

Agree with creed_the_third 100%.

This is absolutely how schools view things. A 3.7 student with a couple of C's in humanities classes is in much better shape than one with C's in calculus.

You generally have to provide transcripts for all courses you've taken, whether as part of a degree or not. However, courses taken as a non-degree seeking student will not influence your undergraduate GPA.

My impression is that companies certainly care about what skills you have, but what they REALLY want is the smartest people they can find. Most decent Masters programs equip you with roughly the same skillset, but being at a top program is a pretty good proxy for smarts/ability.

Your best shots on academic record alone are probably Columbia, Yale, Rutgers, and Purdue. Given your research interests and experience, you might have a chance at Carnegie Mellon.

As I've said before, this is simply untrue for graduate school in biostatistics. Top candidates get into ALL the best places they apply, and there seems to be remarkable agreement between the candidate rankings of various departments. A and B are clearly not independent; if they were, this would imply that knowing that someone was accepted at UW/Hopkins would tell you nothing about their probability of getting in at, say, Pittsburgh, when clearly the probability would approach 1. What I think you're trying to express is that, if C is a variable denoting candidate strength/qualifications, then A and B are independent given C. To the OP, you can basically count Harvard out; their applicant pool is even stronger than UW and Hopkins. I would rate your chances of admission at UNC and Berkeley as OK, but not great. UNC might be your best chance, but you could be looking at an unfunded offer.

I wouldn't read anything into this other than they need the letters to review your file. You should submit them ASAP, because they'll probably start looking at applicants soon and you want to be included among the first round of people being reviewed.

That course they're quoting is a bit unusual in that it covers differentiation, integration, and measure theory in one semester. Typically, these topics span 2-3 analysis courses. I can promise you that few students accepted directly into Wisconsin stat out of undergrad have had a standalone course in measure theory. To the OP, if you haven't taken any real analysis yet, I would suggest taking it before you apply. If you've already taken a traditional undergraduate real analysis course covering sequences and series, differentiation, and a bit of integration, then I wouldn't worry about taking measure theory before next year.

It's more random, typically, though it varies by department. Masters applicants are usually reviewed as they come in, but there may be a longer delay between the actual admissions decision and notification because PhD notifications are often prioritized to ensure that admitted students have time to make arrangements to attend recruiting events in Jan-March.

Huh, I've never heard of UW officially waitlisting people before. It appears they're planning on admitting a lot of students this year, so I suppose a waitlist makes sense.

Not necessarily. Harvard typically admits a 'first wave' of rockstars and then opens up slots as people turn them down (yes, it happens...). But we're probably talking second week of April here.

Sit tight. Depending on the system the school uses, it may be several weeks between the time an application is received and when the admissions committee actually reviews it. Furthermore, most departments use some variant of rolling admissions such that obvious admits and rejects are contacted early, but those on the borderline aren't told anything until the adcom has reviewed most of the remaining applicants (typically by mid-February).

If you're a top 5 canadian school, I think you would stand a decent chance of admission into PhD programs ranked outside the top 10, possibly even in the 5-10 range. Think Carnegie Mellon, NC State, Washington at the top end and Purdue, Michigan, Cornell, Penn State, etc. as decent bets.

There is a huge gap both in the amount and rigor of mathematical coursework between the top handful of biostat places and those ranked outside the top 15. That being said, even lower-ranked places can do a fine job of preparing you to work as an applied biostatistician in industry. What you get at an elite biostat program is the coursework and research opportunities that will position you for an academic position. OP, I think your best bet is to start with a Masters at a quality program; from there, you can decide what type of PhD program would best fit your needs.

Well, that grade isn't optimal, but I don't think it's a killer given the range of places you're applying. This is particularly true if the grade is inconsistent with the rest of your record. As a general rule, the default assumption about a bad grade is that the student simply didn't perform well in the class; unfortunately, class averages and other contextual information generally aren't reported in admissions reports provided to faculty.

I think you will derive the greatest benefit out of becoming more familiar with R. It's something you can learn quickly in a short time (unlike advanced math topics) and will be invaluable in many courses and RA projects (unlike specific biological knowledge).

Most schools want to teach you topics like regression and ANOVA themselves. You are far more likely to get credit for having taken math courses than stat courses elsewhere.

The answer to your question depends a lot on the type of departments you are/will be targeting, and the rest of your mathematical record. Top departments won't be blown away merely because you took a course in measure theory as an undergrad, though a good grade in such a course (eg. A- or A) could certainly help you substantially. If the rest of your math record is a bit sketchy, then a good grade could also help alleviate any concerns about your ability to handle the type of graduate-level math you'll be doing. It's also worth keeping in mind that grading in graduate courses is often more generous than in undergraduate ones, because most programs require their students to maintain a GPA of 3 or above to stay (some programs even require a B or greater in all required courses). So, a merely "solid", class-median performance could net you a grade substantially higher than a 'B'.

The most direct way is to contact the administrator in charge of admissions and let them know that you would like to be considered for Masters admission if your PhD app is unsuccessful.

Students get WAY too worked up about this. I see a handful of apps every year with SOPs referring to another department, and it barely even registers. It would be crazy for a department to reject an applicant merely on the basis of an inadvertent name substitution, and most departments aren't at least somewhat rational in their review of applications.