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I am an international student (Indian), planning to apply for PhD programs in Statistics/Biostatistics this October. I would really appreciate an evaluation of my profile and my chances of getting into some of the places I'm aiming for.

Undergraduate Institution In India (Not ISI/IIT)

Major : Statistics

GPA : 3.94;  Major GPA : 4.0;  WES Evaluated US Equivalent GPA : 3.98.

Graduate Institution : Duke University (Masters in Statistical Science, will graduate this May)

Graduate GPA : 3.97

Undergraduate Courses: I have a more courses in Statistics, and fewer in Mathematics. Math Real Analysis (A), Logic and Set Theory (A), Calculus and Analysis I and II (Both A), Linear Algebra I and II (Both A), Computational Mathematics I and II (Both A). Stats : Probability and Sampling (A), Statistical Estimation(A), Analysis of Variance(A), Applied Statistics I, II, III, IV (All A), Stochastic Processes(A), Linear Models I and II (graduate level, fair amount of linear algebra, both A), Probability Theory I and II(graduate level, both A), Distribution Theory and Estimation I and II(graduate level, both A), Planning and Analysis of Experiments I and II (graduate level, both A).

Graduate Courses at Duke : I took the recommended MS courses, I'm listing some here. Mathematical Statistics (A), Predictive Modeling (A), Bayesian and Modern Statistics(A-), Advanced Stochastic Modeling (A), Causal Inference (A), Spatio Temporal Modeling (A), Study Design (A), Probabilistic Machine Learning(ongoing).

GRE General : V :162, Q:162, AWA :4.5.

GRE Math: Not taken

Research Experience

1. Working since last summer with a senior professor at Duke for my MS thesis (relates to missing data), which will culminate into a first author paper by the time I apply (it will hopefully be in submission by then).

2. Working on a project in Biostatistics since October, but it is more on the data analysis side (analysis of repeated measures EHR data and mixed modeling). We will be submitting to a conference soon.

3. Another project in Statistical Genetics, also more on the data analysis side. I don't expect publications coming out of this.

Schools I will be choosing my schools primarily based on my research interests, which is missing data &/or causal inference, rather than departmental rankings. I would really like to know my chance of being admitted to the following schools (this is not a full list of schools, I'm just listing some dream schools) - UCLA Biostats, Duke Stats,  NCSU Stats,  UW Seattle Biostats, Harvard Stats, UMich Biostats,UPenn Stats. I feel most of these are outside my reach, but would really like honest opinions of what schools I should target.

Letters :  I will be taking letters from my three research advisors from the 3 listed projects.

Concerns :

1. My GRE Quant score. The first time I took it, I was ill on the test day, but still managed to get that much. I did not retake earlier since I thought the score would do for MS programs. 

2. Math subject GRE. I have not taken it before and right now, I don't think I have the time to prep for it. I will be working full time at the time I apply.

I would like to know if I should retake the general GRE and aim for a higher Quant score or  spend time studying for the Math GRE. I don't think I can do both.

Thanks.

 

 

 

 

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Your list is very top-heavy. I don't think you have a chance at Harvard Statistics or UPenn Statistics because your undergrad institution was not ISI or an IIT. UPenn Wharton and Harvard are amazing schools for causal inference, but these schools are very tough to crack (Penn Wharton cohort is only about 4-5 students every year) and only seem to accept those from elite universities.

Your MS from Duke and your MS research will probably help though. I would trim down the list of top-tier schools and maybe only apply to 2-3 of them. I could see you getting into UPenn Biostatistics (not Wharton) or UCLA Biostatistics. For Statistics, you likely have a good chance for schools in the range of UFlorida and UIUC.

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18 minutes ago, Stat PhD Now Postdoc said:

Your list is very top-heavy. I don't think you have a chance at Harvard Statistics or UPenn Statistics because your undergrad institution was not ISI or an IIT. UPenn Wharton and Harvard are amazing schools for causal inference, but these schools are very tough to crack (Penn Wharton cohort is only about 4-5 students every year) and only seem to accept those from elite universities.

Your MS from Duke and your MS research will probably help though. I would trim down the list of top-tier schools and maybe only apply to 2-3 of them. I could see you getting into UPenn Biostatistics (not Wharton) or UCLA Biostatistics. For Statistics, you likely have a good chance for schools in the range of UFlorida and UIUC.

Thanks for the reply ! Do you also think that NCSU Stats and UMich Biostats are a far shot ?

Edited by geekstats
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10 minutes ago, geekstats said:

Thanks for the reply ! Do you also think that NCSU Stats and UMich Biostats are a far shot ?

Those are less of a reach than Harvard or UPenn Wharton but it is hard to ascertain your chances only because the competition among international applicants is very fierce and your undergrad institution was not ISI or IIT. Your paper submissions and your MS from Duke are certainly pluses though, and I think it is worth a shot to try a few "reach" schools like NCSU. 

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Also, you do not need to retake the GRE or the math subject GRE. The subject test is only absolutely necessary for Stanford Statistics (as far as I know) and strongly recommended for UChicago Statistics and Columbia Statistics. I think those schools are most likely outside your reach anyway. The highest I would aim for in your case is NCSU Stat and Michigan Biostat (though if you have the funds and wanted to try UNC Biostat or UWashington Biostat, I suppose it couldn't hurt).

Edited by Stat PhD Now Postdoc
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51 minutes ago, Stat PhD Now Postdoc said:

Also, you do not need to retake the GRE or the math subject GRE. The subject test is only absolutely necessary for Stanford Statistics (as far as I know) and strongly recommended for UChicago Statistics and Columbia Statistics. I think those schools are most likely outside your reach anyway. The highest I would aim for in your case is NCSU Stat and Michigan Biostat (though if you have the funds and wanted to try UNC Biostat or UWashington Biostat, I suppose it couldn't hurt).

Thanks for all the help. I was also wondering if I stand a better chance at Biostats than Stats, considering that my background is light on the pure math courses.

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I will echo the advice that has been given to you. I am an applicant this year and the competition among international students has really struck me very hard. I know people with stellar profiles, who got rejected by top-10 schools. You can increase your chance (significantly) by applying to larger PhD Statistics programs such as OSU, UConn, UF and Florida State. They have good faculty members in missing data and causal inference. Keep in mind that most students actually change their research directions after a few years into their PhDs. Don't bother applying to small programs like Yale, Northwestern and NYU. They have relatively low ranking in US News, but are very difficult to get in due to small admission quota. Apart from NCSU, you can try a few other reach schools like Penn State and TAMU.

With regards to your standardized tests, I would rather try to get a good score in the Maths Subject Test than retaking the general GRE. Most adcoms know that performance in the quant section of the GRE is a bad indicator of success at graduate schools and the 165 will not jeoparize your application. I got 970 in the Maths Subject Test and the adcom at Rice explicitly said that they were very impressed by my performance. I am also pretty sure that the score has helped me to secure several offers at some top-20 schools. The Subject Test is especially useful if your maths background is light and your undergrad institution is not well known in the US. After all, a single PhD student takes a lot of funding, and the adcoms don't want to bet on someone whose records they do not understand. IMO, you should only send your score if you get above 80th percentile.

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dont listen to people who tell you you're not competitive enough to apply to school x. Hire a graduate school admission consultant, about $3000, to help you package your application and shoot for your dream schools. Grad school admission consultants will make sure you take the best swing you can at your dreams. don't shoot your dreams down without giving them a chance to breathe.

Start your grad apps 1 year before the deadlines. It will take a full year if you do it right. Your GPA is stellar for a math degree. Great job on that.

Edited by thecodemachine
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59 minutes ago, thecodemachine said:

dont listen to people who tell you you're not competitive enough to apply to school x. Hire a graduate school admission consultant, about $3000, to help you package your application and shoot for your dream schools. Grad school admission consultants will make sure you take the best swing you can at your dreams. don't shoot your dreams down without giving them a chance to breathe.

Start your grad apps 1 year before the deadlines. It will take a full year if you do it right. Your GPA is stellar for a math degree. Great job on that.

Lol, $3000 for a consultant? I would not listen to this bad advice, OP. Most PhD programs in Statistics in the USA are swamped with international applicants. The top tier programs like Penn, Stanford, and Harvard can take their pick and typically do not consider any applicants who are not from the top 5% of their graduating class at ISI, Peking, Tsinghua, etc. The OP sounds like a strong candidate but the reality for international applicants is they need to be the top students from the most elite schools in their home country in order to have a reasonable shot at these schools (even if they get a Masters degree from a school like Duke in the U.S., that is still not likely enough to overcome the undergrad alma mater issue because graduate school grades are usually more lenient).

We provided the OP with a realistic range of schools they should apply to and even encouraged them to try a few "reach" schools like NCSU (Harvard and Penn Stats would almost certainly be a waste of money though).

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There is really not enough info here to make a complete opinion.  A lot of the top schools are aware of institutional bias in the selection process and many are trying to overcome it. The LORs need to be seen and read.  Is the OP someone who lived in extreme poverty and went on to maximize their opportunities.  Everyone is looking for the next ‘’ the man who knew infinity ‘’.  Everything needs to be reviewed in context                                          

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4 hours ago, thecodemachine said:

dont listen to people who tell you you're not competitive enough to apply to school x. Hire a graduate school admission consultant, about $3000, to help you package your application and shoot for your dream schools. Grad school admission consultants will make sure you take the best swing you can at your dreams. don't shoot your dreams down without giving them a chance to breathe.

Start your grad apps 1 year before the deadlines. It will take a full year if you do it right. Your GPA is stellar for a math degree. Great job on that.

No consultant in this world can fix your transcript and LoR, which are the most important components in your applications. Competition among international students has got to a point where top GPA, prestigious undergrad institution and good LoR can only get you into consideration at top schools. They have many people with perfect GPA, so you need extra things to stand out. To be accepted at those schools, you need strong research experience, excellent LoR from well-known professors, and a bit of luck too. I don't see how a consultant can help you with those. If the OP has $3,000 to spend, I would advice him to use that money and apply to 30 schools across the US News ranking. I am sure that he will get into a few places with that GPA, publication and a prestigious MS. He is certainly competitive for top-40 schools.   

Edited by hnn12
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Don’t listen to people who tell you somethings not possible. I had a 3.1 undergrad gpa and I got admitted to the number one school for computer science with a consultants help. With your exceptional grades, you’ve got an even stronger platform than I had. Haters are going to hate and try to keep you from out achieving them. Prove them wrong.

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9 minutes ago, thecodemachine said:

Don’t listen to people who tell you somethings not possible. I had a 3.1 undergrad gpa and I got admitted to the number one school for computer science with a consultants help. With your exceptional grades, you’ve got an even stronger platform than I had. Haters are going to hate and try to keep you from out achieving them. Prove them wrong.

Computer Science admissions is very different from Statistics. In CS, a publication or two in a top conference and reference letters from professors who have strong connections to the lab PI's indicated in the application/statement of purpose can greatly mitigate a lower GPA. But this is not the case at all for Statistics.

In Statistics, prestige of undergrad institution and undergrad GPA play a critical role for international applicants, and a 3.1 undergrad GPA would make it impossible for *any* applicant (international OR domestic) to get into the top-tier Statistics PhD programs, even with a Masters degree (this ugrad GPA would not preclude them from getting into a school in the range of 20-50 though, given strong performance in a Masters program). I think someone who is in the actual field of Statistics would know better than you.

Edited by Stat PhD Now Postdoc
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1 minute ago, Stat PhD Now Postdoc said:

Computer Science admissions is very different from Statistics. In CS, a publication or two as an undergrad in a top conference and reference letters from professors who have strong connections to the lab PI's indicated in the application/statement of purpose can greatly mitigate a lower GPA. But this is not the case at all for Statistics.

Statistics, prestige of undergrad institution and undergrad GPA play a critical role for international applicants, and a 3.1 undergrad GPA would make it impossible for *any* applicant (domestic OR international) to get into the top-tier Statistics PhD programs, even with a Masters degree (this ugrad GPA would not preclude them from getting into a school in the range of 20-50 though, given strong performance in a Masters program). I think someone who is in the actual field of Statistics would know better than you.

Do you mean like an actuary? I hear they’re good at statistics.

to the op, no ones saying it’s going to be easy. Your job is to take the best swing possible at your dream schools and finding someone who specializes in grad admissions is a great way to leap far above your competition. Grad admissions is complex and nuanced and I would never recommend applying without an experienced guide to help them through every step. But for sure the internet does not equate to actionable advice.

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14 minutes ago, thecodemachine said:

Do you mean like an actuary? I hear they’re good at statistics.

to the op, no ones saying it’s going to be easy. Your job is to take the best swing possible at your dream schools and finding someone who specializes in grad admissions is a great way to leap far above your competition. Grad admissions is complex and nuanced and I would never recommend applying without an experienced guide to help them through every step. But for sure the internet does not equate to actionable advice.

No, they should take advice from someone who is working in academic statistics and is intimately familiar with the admissions process for statistics, like a stat/biostat professor, postdoc, or current Stat PhD student. The admissions process in Statistics is completely different from that of Computer Science. My advice echos that of other professors from the departments I have been affiliated with and other professors on this forum, and many posters on this board would tell you that my predictions of their chances were spot-on (some even messaging me personally to thank me and tell me where they were going to attend).

My advice is totally objective, not borne of being a "hater." If the OP had indicated that they attended ISI for undergrad, I would have recommended that they aim for Harvard and Penn Wharton Statistics. Given that their alma mater was not ISI, this would ultimately be a waste of money.

Even at my mid-tiered ranked stats PhD program,  many international applicants from China and India were automatically rejected if the adcom had never heard of the undergrad institution. However, this could be overcome with a Masters degree from a respectable program in the US or Canada.  At top-tier programs, however, it is basically impossible for international applicants who did not complete their undergrad at the top schools in their home countries to get admitted.

Edited by Stat PhD Now Postdoc
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What are your opinions about Brown Biostats, Minnesota Stats, UT Austin Stats and  some of the lower UCs, like UCI and UC Davis ? These seem to be mid-tiered on the US news list.  I was wondering if their PhD programs are really small or if they are fair targets for my profile. 

 

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  • 5 months later...

I did have my profile evaluated a while ago, but there are some changes and updates and I'd like to know if the schools I've finalized are reasonable aims. A shout-out to @Stat PhD Now Postdoc and anyone else who'd like to comment.

Undergraduate Institution In India (Not ISI)

Major : Statistics

GPA : 3.94

Graduate Institution : Duke University-- MS in Stats

Graduate GPA : 3.97

Undergraduate Courses:

Calculus I,II (Both A), Discrete Math I and II (Both A), Calculus and Analysis I and II (Both A), Linear Algebra I and II (Both A), Computational Mathematics I and II (Both A).

Probability Theory (A), Statistical Estimation(A), Statistical inference (A), Linear Models I and II (graduate level; B+ and A; one grade really suffered due to illness, will explain this), Distribution Theory and Estimation I and II(graduate level, both A) and a bunch of applied stats courses with As.

Graduate Courses at Duke : Mathematical Statistics (A), Predictive Modeling (A), Bayesian and Modern Statistics(A-), Advanced Stochastic Modeling (A), Causal Inference (A), Spatio Temporal Modeling (A), Study Design (A), Probabilistic Machine Learning(A) and a couple independent studies.

GRE General : V :162, Q:162, AWA :4.5.

GRE Math: Not taken

Research Experience

Wrote a Masters thesis, did some research work in Stat.genetics and Bayesian ML. Also some applied work in analyzing EHR data and stats education.

3 methodology papers in submission to reasonably good journals (~CSDA & Bioinformatics). First author on one, second and third author on the others. One conference presentation in stats education.

Currently doing research in environmental epidemiology at a med school.

Letters : One from thesis advisor (also submitted a 1st author paper with him), one from stat.gen research supervisor (third author paper with him) and one ind.study supervisor.

Schools:

Biostat PhD--UNC, Michigan, UCLA, Emory, UPenn, MD Anderson, UPitt

Stat PhD -- NCSU, PSU, OSU, TAMU, UFL, UConn, FSU

Concerns:

1. Are any of the listed schools absolutely outside my reach? Do I need more safeties?

2. How will a B+ in linear models affect my application? I hadn't  mentioned this in my earlier profile evaluation---but this is the only B I have which was  a result of being ill on exam day. I got an A in part II of the same course the next semester.

3. Is it worth throwing an app to Washington Biostat? Or is it aiming too high?

Edited by geekstats
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19 hours ago, geekstats said:

I did have my profile evaluated a while ago, but there are some changes and updates and I'd like to know if the schools I've finalized are reasonable aims. A shout-out to @Stat PhD Now Postdoc and anyone else who'd like to comment.

Undergraduate Institution In India (Not ISI)

Major : Statistics

GPA : 3.94

Graduate Institution : Duke University-- MS in Stats

Graduate GPA : 3.97

Undergraduate Courses:

Calculus I,II (Both A), Discrete Math I and II (Both A), Calculus and Analysis I and II (Both A), Linear Algebra I and II (Both A), Computational Mathematics I and II (Both A).

Probability Theory (A), Statistical Estimation(A), Statistical inference (A), Linear Models I and II (graduate level; B+ and A; one grade really suffered due to illness, will explain this), Distribution Theory and Estimation I and II(graduate level, both A) and a bunch of applied stats courses with As.

Graduate Courses at Duke : Mathematical Statistics (A), Predictive Modeling (A), Bayesian and Modern Statistics(A-), Advanced Stochastic Modeling (A), Causal Inference (A), Spatio Temporal Modeling (A), Study Design (A), Probabilistic Machine Learning(A) and a couple independent studies.

GRE General : V :162, Q:162, AWA :4.5.

GRE Math: Not taken

Research Experience

Wrote a Masters thesis, did some research work in Stat.genetics and Bayesian ML. Also some applied work in analyzing EHR data and stats education.

3 methodology papers in submission to reasonably good journals (~CSDA & Bioinformatics). First author on one, second and third author on the others. One conference presentation in stats education.

Currently doing research in environmental epidemiology at a med school.

Letters : One from thesis advisor (also submitted a 1st author paper with him), one from stat.gen research supervisor (third author paper with him) and one ind.study supervisor.

Schools:

Biostat PhD--UNC, Michigan, UCLA, Emory, UPenn, MD Anderson, UPitt

Stat PhD -- NCSU, PSU, OSU, TAMU, UFL, UConn, FSU

Concerns:

1. Are any of the listed schools absolutely outside my reach? Do I need more safeties?

2. How will a B+ in linear models affect my application? I hadn't  mentioned this in my earlier profile evaluation---but this is the only B I have which was  a result of being ill on exam day. I got an A in part II of the same course the next semester.

3. Is it worth throwing an app to Washington Biostat? Or is it aiming too high?

I think your list of schools sounds very reasonable, and I think you should be able to get into some of those Biostat programs, particularly the lower-ranked ones who will highly value your research and the fact that you submitted three methodological papers to reasonably good journals. I think the B+ you received in Linear Models I is partly offset by your A in Linear Models II.

It may be worth applying to UW Biostat for good measure.

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