statsnow

It depends on a lot of factors. What schools did you go to? Are you a domestic or foreign applicant. Are you an URM? What will your LOR say and who are they from. Grades and classes alone are only part of the evaluation. How old are you? Have you had any jobs or internships and if so from whom?

Rubin retired and went to china so Harvard has lost a lot of its causal inference focus

I think Harvard is a much better biostats program than Berkeley biostats. I think Berkeley stats is a better program than Harvard stats. If you are dead set on biostats go to Harvard. However getting a degree in stats gives you more flexibility. Depending on what you want to do, going to Berkeley gives you more options for the future.

Not that any of this matters now but when Friedmans paper was published he was at Berkeley where he got his Phd. I agree for theoretical statistics that Stanford is the best now. However when it comes to many other areas of statistics including applied statistics, causal inference etc I believe Berkeley is better. Berkeley is also much better when it comes to diversity. The world only needs so many theoretical statisticians I am a strong believer that the best place is where you feel the most comfortable no matter where that may be.

Actually gradient boosting came from Berkeley from Leo Breiman if history is correct. Freidman also got his phd at Berkeley . Bartlett who is at Berkeley now developed functional gradient boosting which is a more general concept. It was developed at the same time Friedman published his papers. I dont really think you can say that one group revolutionized the field if you look at all the historical facts

@statsGod I think if you want to learn theoretical statistics you are probably correct about Stanford. However a department is not totally defined by a few stars. There are other factors that go into an education . Michael Jordan is the leader in artificial intelligence and a few other areas. That is greatly valued by many people. Practical application of statistics and methodology is important to very many people. I am not sure there are many people at Stanford that do Causal Inference. Departments hire by what is their perceived needs and that can vary from year to year. Also the lack of diversity at Stanford can and has been seen as a negative by many people.

Not so sure why people think stanford is better than berkeley. It is a smaller department than berkeley. It is mostly theoretical. Berkeley has much closer ties to EECS and does a lot more applied and methodological research Not getting into the politics of this however A lot of people have complained about the lack of diversity at stanford. I have heard many female applicants accepted at Stanford have rejected it because of its diversity reputation. I am not sure if they have ever had a black or Hispanic phd student at stanford.

@bayessays I think a lot of people would disagree with you that Stanford is #1 by a mile. A lot of people for a variety of reasons think Berkeley is far superior. What do you base your opinion on? Also there are a number of differences between the schools in the top ten.

Look at the new head of the cdc Rochelle Walensky and whom she works with. She has been pretty active

Lower division means the course number is less than 100 at cal. 100 to 199 means upper division and 200 and above is graduate level. Berkeley wants to know what you actually learned. Telling them the text books and syllabus you went through is helpful. Beginning ODE and linear algebra are generally considered lower division classes

MrKrabs what I would do is ask for the names of former CSU students who were in their PHd statistics programs. I would ask for UCI, UCLA, Davis and Berkeley. That is proof one way or the other. I have heard reasons why this happens but I would prefer not to say in an open forum. I dont think it is fair if my information is correct. The selection process will also change this fall if prop 16 passes in November. Best of luck to you.

Unfortunately many of the UC stats programs don’t like to take CSU students. I think it is unfair for a variety of reasons. You should be aware of this bias so you can counter it Maybe some of the other posters have suggestions

Insert_name I think your advice is really good but nothing is guaranteed for the top 5 programs. At that level I think alot is about fit and what they want their group of grad students to look like

I agree with what Bayessays and Stat Asst Professor have to say. I spent 4 summers at FAANG and the experience was well received. It is always a plus to have good coding skills. Remember too that alot of the good people who get their phds go back into industry or some spend a bunch of time consulting with industry after their PHd. The industry money temps alot of people. It also helps being a domestic URM . At this point I dont think you need to spend more time working on your research portfolio. I think alot of schools will take you

I am familiar with a couple of schools waiving the general GRE. You should check with the individual programs

I agree it’s very uncommon to see published research in a top journal before you start your PhD. Also with multiple authors sometimes it’s difficult to tell what the student contributed to the paper.

In the top 10 no one is a guarantee. It is all about fit. Lots of schools look at that closely. Apply where you think you will the happiest. Some schools this fall are not using the GRE at all for admissions

“The job candidate did go to one of the top 15 schools (according to the USNWR rankings).” @Stat Assistant Professor One last question. What was her research area? Was she applied, theoretical or methodological?

@Stat Assistant ProfessorI don't think working with an Assistant Professor is necessarily an issue. There was one job candidate on the job market in the 2019-2020 hiring cycle who got like, 20 interviews, and her advisor was an Assistant Professor. She also got offers from UIUC, UNC, UFlorida, UMinnesota, Columbia, and probably others as well What was the profile of this candidate?

I have a variation on the original question. Some of the posters seem very knowledgeable in this area. If someone attends a top 10 stats program what do the schools look for if the applicant wants a tenure track research based assistant professorship at an R1? Do teaching skills matter? Is there any way to bypass a postdoc these days and go straight into an AP? Is there any way to quantify how many publications and in what journals are needed for the AP? How much do LORs really matter?

To clarify what bayessays just posted. Jordan is not the only professor that does ML at Berkeley. There are probably at least 30 professors and countless more postdocs involved in some form of ML at Berkeley.

I have familiarity with Berkeley. Berkeley is consistently rated number 1 or 2 in stats, math and CS. Berkeley stats is much bigger than CMU. There is an extremely close tie between EECS and stats at Berkeley. Many of the stats professors have joint appointments with EECS. Berkeley also has close ties with Stanford, Harvard and Silicon Valley. It is extremely easy to get a summer internship in Silicon Valley because of its close ties. Those internships can pay around 10k per month. Berkeley has lots of young faculty that are eager to work with new students . Look at Ding, Feller, Fithian, Pimental and Steinhardt. In addition there are a number of postdocs at Berkeley. Berkeley has almost 4 times as many postdocs as CMU. Most students at Berkeley have two or more advisers. There is lots of flexibility in terms of selecting your advisers. They do not all have to come from the stats department. Many students wait a couple of years to pick their advisers. There is also no qualifying exams at Berkeley. There are no prescribed classes that need to be taken . Many students easily move across research areas. And it fact it is strongly encouraged at Berkeley In terms of ML Berkeley is consistently rated at the top along with CMU. You may want to look at the Yu group or BAIR. Berkeley Artificial Intelligence Research has 30 professors associated with it and over 200 grad students and post docs. BAIR is doing cutting edge research in a multitude of areas In terms of flexibility I dont think there are departments that come even close to Berkeley.