DanielWarlock

I completely agree with doc's assessment. In fact, I can observe this trend at Harvard. The inference class this year is taught from a range of relatively modern topics instead of unnecessarily rigorous proofs on consistency and normality of MLE/UMVUE/NP tests and stuff like that. The measure theoretic has been downplayed a lot at Harvard as well because it is "almost completely useless". That said, the classic asymptotic techniques are still very useful. When you write some research paper, it is expected that you will give some bounding statements with *NO* exceptions and the toolkit/intuitions for doing that is pretty standard from the classics.

I'm not exactly sure about biostatistics jobs. But in finance, school names carry great weight for master/undergrad level jobs. This is called "target schools". If you are not from "target schools", your resume is placed into trash unless you have some connections in the firm. Even though people laugh at Columbia's master program as a "cash cow" but when I interviewed at banks in NYC, there are always severals students come from there. Some of those guys barely speak English and I suspect they are very good. But they are on equal footing with someone from Stanford, for example, when they got on-site interviews by Columbia name. On the contrary, I rarely see anyone from unknown state schools. It requires a great amount of networking to even get an interview if you go to Pittsburgh, which Columbia name will automatically grant you.

Man Are you from Fudan mathematics? I really want to go to Columbia. I'd like to trade my offers at Harvard or Berkeley for Columbia, if only it is possible. It is so brutal..

I don't know anything about UW. But Chicago does take some of its master students towards its PhD program. The rumour is that Chicago is insanely tough. It could potentially be a good thing if you are young and have no family obligation--you just go there and fight for your life, so to speak. But if you are anything like me, you will think twice before committing to Chicago.

Columbia, NYU, Yale are all not "top top tier". They are of medium to low tier in terms of competitiveness. In fact, Columbia master program admits like 500 students per year. PhD and masters have different focus. That may be why you struggle with PhD application more.

The OP doesn't have perfect test score. It is only his/her hypothesis. Likely OP will get suboptimal GRE. OP's GPA is also very bad, to be blunt, for the top master programs. That said, OP has good working/research experience--if the letters are as good as OP claims, the chance is better. But I don't think Stanford is a possibility for OP since there are only 8 globally admitted. UChicago is a huge stretch also. I applied to both programs and was rejected and my stats then was much better than OP. Columbia is easier from what I heard as a "cash cow program" but I didn't apply. I interviewed with a few guys there at a bank during my old life. They appeared to be very strong quantitatively so OP may still fall short but I'm not certain. @bayessays I have first-hand experience with PhD and master applications. And I will say master application is no less competitive than PhD at top venues. For example, Harvard data science master probably has lower admission rate (5%) than the PhD program (10%), although the focus certainly differ.

Your GPA is too low and you struggled with basic math stats class on undergraduate level. I would caution you applying to Chicago and Stanford. Even if you are admitted, you will be having problems completing the course requirement.

I don't know much except that Prof. Kou, Murphy at statistics department are affiliated to public health. So they can potentially be your advisors. Kou is insanely good with theory/methodology. He invented equi-energy sampler and can recite theory of point estimation which is like crazy. I suspect that he knows a great deal about geometry -- it is very cool if you are math-inclined. In fact, Kou graduated from Peking university math and went to Stanford himself for a PhD. This means if you go for him you can get a stanford education at Harvard. Lol. Don't know much about Murphy.

You can get as rigorous as you want at Harvard but only if you choose to do so. The idea of Harvard and Stanford differ in that Harvard does not intervene and disrupt your own plan for your own education. For someone who does not have a plan though, Stanford is better. The admission at Stanford is more selective too. That said, almost half of the faculty here at Harvard graduated from Stanford: Jason Lucas, Joe Blistzten, Sam Kou, and the newly hired random matrix assistant prof Sen. It is as if you get a Stanford education at Harvard. Very cool if you think about it. Can also do a JD or MD as joint degree at HLS or HMS if you stay here for PhD.

Are you a foreign students? Because Purdue math is one of the very top. Yitang zhang who solved a big problem recently graduated from there. Probably not as good as Princeton but still the very best ones out there.

Nothing for me. But I'm just waiting for Columbia. Anyone heard anything? Seems like a bunch of guys got interviews. Do they always need to interview people? Is it over?

Current master student at Harvard (not exactly data science but CSE which is almost identical to data science program and I know everyone here). A lot of people will tell you to go to Stanford. But do that only when you are certain you can handle their courses--it is much harder than Harvard requirement by a long mile. Also Stanford does not support you doing thesis though that remains an option--the timetable won't allow it (unless you are insanely good). So I went to Harvard, and for 1 and half years I only took 2 classes per semester and did a lot of research. Now I got into Berkeley and Harvard for PhD in statistics, which may not be possible or much harder to do with Stanford.

I was rejected from UF this morning. I'm actually very curious of how all admission works. My profile got me into several top 10 programs but not good enough to get me into UF, Minnesotta, Michigan which are ranked much inferiorly? I have very good interests match with UF faculties. This makes me wonder.

I feel that there has been too much aggression and negativity. Technically, you are getting paid to learn stuff, which seems to me a pretty good deal. I used to work. At that time, I needed to do research and read paper after 7pm--I just wanted to sleep and I felt terrible. For my masters, I essentially pay tens of thousands to take same classes with PhD and do research with less support. What are we even complaining about here? I'd still do PhD if I were to go back to my old job after that.

Hello. I had a similar dilemma about 2 and half years ago when I also worked in finance as a "quant analyst". Look. It sounds good to be a "financial quant". But the truth is that the work is pretty routined and most of your co-workers are disillusioned: they either do it really half-assed so that they can spend more time with their family, or they become "workaholic" in order to be promoted. After a while, you feel that you want to get away from this. I'm not saying that "financial quant" is not good. On the contrary, it has several upsides as mentioned by Bayessaid. But the decision solely hinges on whether you like creative work. This is important. If you are a guy who just wants to do routine stuff and stay relaxed, then academia is not for you: you will need to not only work hard but think hard and stay active. But if you enjoy the freedom of exploring things, then you should do it. This is what I thought 2.5 years ago. I basically thought about it and quitted my job. I then contacted a prof and started doing research. Simple as that! You just need to make a decision if you want to change. You can start your research career today if you want. *Also a correction on opportunity cost: a "financial quant" typically makes 100K-500K and a PhD makes 30K. Over five years, it is 0.35M-2.35M lost. So you can lose as much as a 2 million! Thanks.

Looks like they are sending out offers? But only one guy reported... Not sure but not looking good. Does anyone else get an offer?

Does anyone here get interviews from Columbia? I saw another person posting interview invite on results page. Is interview a necessary step to Columbia admission?

Technically, there is still "hope" but my feeling is that once you do not receive offer and others do, you are waitlisted. You see, Duke sent nearly 30 offers (I saw it from their mailing list). For example, I'm just officially confirmed to be waitlisted by Michigan but I knew that a few days ago-- some people here even argued with me about this back then. For me, same thing is now going on with UFlorida, Minnesota and Columbia where others already got offers/interviews while I didn't. I'm hopeful for Columbia because there is just one guy who got interview and it is possible that candidates will be admitted without an interview (when they deem interview to be unnecessary for such candidates for example). But hope is not very, very high at this point.

I mean, if 10+ people report here, then you know offers are all out and is almost surely in higher number than what they expect to enrol. For example, I can see Duke sent 30+ people offers from the emailing list. I personally would take it as "denied" but you can have your personal interpretation as well.

Hello, you can see on gradcafe results section that they have sent offers to at least 10 people.

No but apparently the offers were out yesterday or the day before.

Anybody hears back from Columbia? Looks like I was waitlisted by Michigan! A little nervous.

Thank you so much for the reply. I have heard of Blei and Jordan of course. Andrew Gelman seems to be another prominent Bayesian at Columbia. But do I have a sure chance of securing these people as my supervisor though? I know at Harvard PhD students can pretty much talk to and work with any faculty they want and there is flexibility--a primary supervisor is not set until like the 3rd year. But how does phd supervisor match typically go at other places?

I have currently received offer from Duke, Berkeley and Harvard. The only school I will consider over these but have not heard from now is Columbia because of geographic proximity (my family is located at NYC). I would deeply appreciate opinions and advice on choosing between these 4 programs. The following is my situation and concerns: Research interest: computational statistics and applied probability. I'm not dead set on any particular topics at this point. Currently I work on Monte Carlo (MCMC, SMC etc.) But I would be interested to work with Bayesian, non-parametrics, or applied probability such as random matrices, stochastic process. More applied topics such as machine learning, deep learning, high-dimensional statistics would be appealing to me as well. I'm not dead set to go into academia; research positions in industry (tech companies such as Microsoft research, Google Deep mind etc.) are appealing to me as well but it seems that they tend to go for people with a particular types of skill set. For example, an expert in MCMC may not be particularly suitable for industry positions. Other academic concerns: How difficult/stressful is the curriculum and qual exams in each department? And how stressful in general is each department? I know Harvard is more laid back but not sure about the others. I'd prefer to go to a place where people are not stressed out all the time--that's why I didn't apply to Uchicago and Stanford in the first place. If someone can comment on department culture at Columbia, it would be particularly useful. Personal: I'm based in NYC with my wife and do not like to go too far away to the west coast and this is why I hesitate choosing Berkeley despite the research interests there seem most diverse. This is also why I would strongly consider Columbia. Note: I will go to visit days for sure. But it is good to hear opinions on this forum as well.

I never intend to initiate any hostile personal attacks. I give my personal opinions on people's profiles and comments made. In this case, I give my reasons why I disagree with the commentator's claim regarding abstract algebra. It is not responsible to encourage someone ("why not") with stats background to take honour abstract algebra classes because "it is just binary operations and not too difficult". I myself made this mistake in college and was almost not able to graduate on time to attend my master program. In the other instance you mentioned, I observed that there are issues with the person's written English and cautioned him about not finding a proof-reader. This advice is based on my personal experience as a non-native speaker. It is also in the context of his unusual GRE verbal score. It is supposed to be a reminder and not a hostile attack. But there seems to be some misunderstanding on my part, too. I did post a lot more than I should and some of those comments are heavily opinion-based. I apologize and will refrain from posting comments henceforth. Thank you.