orchidnora

Hi, everyone. Does anybody have any information to compare these schools? I am very excited to have been accepted to these amazing schools and never expected I would have to make such a decision. Berkeley has been my top choice for a while for various reasons. But I want to be cautious and evaluate all my options carefully. I will definitely be visiting Duke and Berkeley to help decide, but I'm not sure if I want to attend UW. Any information about these schools (especially UW, since I'm less familiar with their program) would be helpful for me. 

They're all amazing schools, so bring your decision down to research fit and location.  If you want to do Bayesian stuff, obviously go to Duke.  If you're interested in ML, UW has some great ML people (Emily Fox and Witten) as does Berkeley (Jordan). I'd visit and follow your gut. You can't go wrong. 
If you are choosing between programs that are current ranked 12 and above on US News (Stanford, Berkeley, Washington, Harvard, Chicago, Duke, CMU, Michigan, UPenn), I don't think there is a one size fits all answer. 

UW is particularly strong for social science statistics and analysis of network/spatial data. It also has a few outstanding researchers in the machine learning (both theoretical foundations and methodology/applications).

Hi, everyone. Does anybody have any information to compare these schools? I am very excited to have been accepted to these amazing schools and never expected I would have to make such a decision. Berkeley has been my top choice for a while for various reasons. But I want to be cautious and evaluate all my options carefully. I will definitely be visiting Duke and Berkeley to help decide, but I'm not sure if I want to attend UW. Any information about these schools (especially UW, since I'm less familiar with their program) would be helpful for me. 

Hi, everyone. Does anybody have any information to compare these schools? I am very excited to have been accepted to these amazing schools and never expected I would have to make such a decision. Berkeley has been my top choice for a while for various reasons. But I want to be cautious and evaluate all my options carefully. I will definitely be visiting Duke and Berkeley to help decide, but I'm not sure if I want to attend UW. Any information about these schools (especially UW, since I'm less familiar with their program) would be helpful for me. 

Hi, everyone. Does anybody have any information to compare these schools? I am very excited to have been accepted to these amazing schools and never expected I would have to make such a decision. Berkeley has been my top choice for a while for various reasons. But I want to be cautious and evaluate all my options carefully. I will definitely be visiting Duke and Berkeley to help decide, but I'm not sure if I want to attend UW. Any information about these schools (especially UW, since I'm less familiar with their program) would be helpful for me. 

Hi, everyone. I'm supposed to be making lists of potential advisors at schools I'll be visiting. Some of the professors with whom I have the best research fit seem to be very busy people. Some have 10 or more students and postdocs. Does anybody have experience with or insights on working with very busy advisors? Thanks! 

Hi, everyone. I'm supposed to be making lists of potential advisors at schools I'll be visiting. Some of the professors with whom I have the best research fit seem to be very busy people. Some have 10 or more students and postdocs. Does anybody have experience with or insights on working with very busy advisors? Thanks! 

Hi, everyone. I'm supposed to be making lists of potential advisors at schools I'll be visiting. Some of the professors with whom I have the best research fit seem to be very busy people. Some have 10 or more students and postdocs. Does anybody have experience with or insights on working with very busy advisors? Thanks! 

I think you should also post your budget, keeping in mind that some departments/advisors might provide you with a work computer or funding for one as well. 
One thing that's nice about Mac is that the hyperthreading can be easily exploited in R through the "parallel" package. Using the "parallel" package, you can easily speed up certain types/sections of code drastically. This is convenient if you plan on running your code locally. 
If you get into heavily computational work, then you will be probably be mostly working on HPC. In that case, the quality of your computer doesn't matter as much (a $500 laptop would suffice), as long as you can connect remotely to the HPC server. Connecting to the server is obviously easier through Unix, but there are programs you can download to access it through Windows too. 
Personally, I like working locally in RStudio as well as using HPC, so I did recently buy a nice ASUS laptop with Windows. I would have liked a Mac, but a Mac with similar specifications is far outside my budget.

I think you should also post your budget, keeping in mind that some departments/advisors might provide you with a work computer or funding for one as well. 
One thing that's nice about Mac is that the hyperthreading can be easily exploited in R through the "parallel" package. Using the "parallel" package, you can easily speed up certain types/sections of code drastically. This is convenient if you plan on running your code locally. 
If you get into heavily computational work, then you will be probably be mostly working on HPC. In that case, the quality of your computer doesn't matter as much (a $500 laptop would suffice), as long as you can connect remotely to the HPC server. Connecting to the server is obviously easier through Unix, but there are programs you can download to access it through Windows too. 
Personally, I like working locally in RStudio as well as using HPC, so I did recently buy a nice ASUS laptop with Windows. I would have liked a Mac, but a Mac with similar specifications is far outside my budget.

Thanks to all for the insights! I never would have guessed that Michael Jordan DOESN'T come from a math/stats background. That really puts it into perspective for me. Since I am mostly interested in computational stats/ML, it makes sense more sense now that I've been drawn to these professors with strong ties to EE/CS. I've been looking at the journals potential advisors publish in, as well as the student job placement, and now I feel more confident about my choice of advisors. 

Thanks to all for the insights! I never would have guessed that Michael Jordan DOESN'T come from a math/stats background. That really puts it into perspective for me. Since I am mostly interested in computational stats/ML, it makes sense more sense now that I've been drawn to these professors with strong ties to EE/CS. I've been looking at the journals potential advisors publish in, as well as the student job placement, and now I feel more confident about my choice of advisors. 

Goodness! IIRC, one of you guys went to Duke, took a bajillion graduate-level math and statistics classes and published several papers as an undergrad, yet only got waitlisted at Stanford? Another applicant that I've been messaging with personally on thegradcafe also went to Harvard and took graduate courses there, but got rejected from Stanford. They must really weigh the Mathematics Subject GRE more heavily than I had thought. Personally, I question the relevance of it for Statistics, but I guess when you have so many qualified applicants, it does serve as one method for paring down the list of applications.

Thanks to all for the insights! I never would have guessed that Michael Jordan DOESN'T come from a math/stats background. That really puts it into perspective for me. Since I am mostly interested in computational stats/ML, it makes sense more sense now that I've been drawn to these professors with strong ties to EE/CS. I've been looking at the journals potential advisors publish in, as well as the student job placement, and now I feel more confident about my choice of advisors. 

I agree generally with what Stat now has to say.  Sometimes the analysis of the right fit needs to go a little deeper.  Michael Jordan is incredibly brilliant and has lots of students. He is also very busy.  It is therefore difficult to get facetime with him if he is your advisor.  Sometimes it is better to take an advisor who can spend more time with you.

It matters most what journals or conferences they are publishing in and what their reputation in the statistics community is, not what their degree is in. For example, Michael Jordan from UC Berkeley is a very well-renowned researcher in both Statistics and Computer Science, even though his PhD is in Psychology/Cognitive Science -- Jordan later switched his research field from psych to mathematical statistics and machine learning... kind of random, but he was a smart guy, and I guess he taught himself statistics, because he pioneered some fields of statistics that are very active research areas (namely, in topic modeling, variational inference, and Bayesian nonparametrics). Michael Jordan's lab and his PhD students/postdocs consistently publish in top statistics journals like JASA, Annals of Statistics, etc. as well as a top CS conferences like NIPS, so working with Dr. Jordan would absolutely be very good for someone's job prospects (I know some of his former PhD students have gone straight from PhD to TT faculty at places like MIT).
I would take a look at what venues these faculty members are publishing in and what the job placements of their former PhD students are.

I don't think it matters what their degree is in. Especially if you're doing ML type work, practically the gap between a CS/applied stat/ML PhD can be very small/non-existent.

If they are mainly in the non-statistics department and have an honorary connection to the statistics department, they're probably not the best choice.  I'd look at what journals they're publishing in.  For example, a professor who does non-statistics related computer vision research and has a courtesy appointment in stats is not a good choice if you want a job in a statistics department.  If you work with Kosuke Imai at Harvard, who has a PhD in political science but is a king of causal inference, you'd probably have better luck.   It's not about their degree - it's more about how likely they are to be doing the research that gets you a tenure-track job in a stats department.

I was waitlisted at Stanford, but did not receive anything from Berkeley.

Congrats to all who got accepted to Stanford! I still haven't heard anything from them. 
However, I woke up to an email this morning from UC Berkeley! I've been accepted!! I'm beyond ecstatic, considering that Berkeley was my top choice school. 

Congrats to all who got accepted to Stanford! I still haven't heard anything from them. 
However, I woke up to an email this morning from UC Berkeley! I've been accepted!! I'm beyond ecstatic, considering that Berkeley was my top choice school. 

Congrats to all who got accepted to Stanford! I still haven't heard anything from them. 
However, I woke up to an email this morning from UC Berkeley! I've been accepted!! I'm beyond ecstatic, considering that Berkeley was my top choice school. 

Congrats to all who got accepted to Stanford! I still haven't heard anything from them. 
However, I woke up to an email this morning from UC Berkeley! I've been accepted!! I'm beyond ecstatic, considering that Berkeley was my top choice school. 

Congrats to all who got accepted to Stanford! I still haven't heard anything from them. 
However, I woke up to an email this morning from UC Berkeley! I've been accepted!! I'm beyond ecstatic, considering that Berkeley was my top choice school.