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2020 Statistics PhD application chances

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I finished my masters in Data Analytics in May. Now I want to go for a PhD in statistics.


Computer Science at Illinois State University

GPA 2.9, 3.3 in major

Good grades in CS classes (As & Bs) not as good in math classes for my (unfinished) minor. One repeat and one D.


Data Analytics at University of Illinois Springfield

GPA: 3.7

GRE (from four years ago): Verbal 166 (97%), Quant. 157 (64%), Writing 3.5 (39%) -- I plan to take this again in September and will study more for the Quant portion!

Master's closure project in machine learning and natural language processing.

LoR: One confirmed from master's capstone class, pretty sure he was impressed with my project/work. Could ask for one from manager at on-campus min. wage job. Her letter might be relevant for a TA position... Not sure about #3...

Research: None really. My MS program was entirely focused on getting a job. (Only one prof ever mentioned his research!)

My research interests are in machine learning and creating new algorithms using statistics.

My top choice is Univ of Illinois UC. Should I apply to the MS program and switch after a year? Or is there a chance of acceptance into a PhD program?

If it matters I'm a female domestic, Illinois resident.

Thanks for any advice!



Edited by GeekySarah
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You should get letter-writers that convince the schools that you are good at high-level math and might be good at research.  As important as TA's may be at many universities, you're not going to get into a PhD program because you'd be a good teacher.

Even so, with my apologies, I don't think you would get into a statistics PhD program if you applied with your current profile.  Your quantitative GRE score is too low, as you know.  I'm guessing from your master's program title that it didn't include real analysis, and unless you took that and did very well (in grad school or undergrad), you're gonna have a really tough time getting into a PhD program (and you'd need a 163 or so on the qGRE to go along with it).

If you want a PhD in statistics, you'd want to take real analysis and a probability/statistical inference/mathematical statistics sequence and do really well.  That might be in a statistics master's, or maybe as postbacc classes, but that would be a start, along with a higher qGRE score and maybe finding some research experience along the way.

I'm hardly an expert, so if an older poster contradicts me then you should listen to them, but this is probably a good start.  I'm sorry in the present, and I wish you good luck for the future.

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Your route to a PhD program is going to be pretty tough and you would definitely need a MS first to have a chance at getting in.  You need to prove that you can get As in classes like real analysis and a MS-level prob/stat class.  You also need to improve your GREQ significantly - as of now, you might struggle getting into an MS program.  I don't really see a route for you getting into a ranked program.

I do not want to sound condescending here, so please do not take this the wrong way, but have you looked at what getting a statistics PhD really entails? You will be doing advanced math, orders of magnitude harder than your undergraduate classes, for hours every day.  Some people get Cs in undergrad math classes because they're lazy, or a 157 on their GREQ because they have trouble taking tests, but if these are truly representative of your math ability, a PhD in statistics is not going to go well.  Many people (who got all As in undergrad and high GRE scores) start a PhD in statistics because they like analyzing data and then end up quitting because they can't handle the math. I don't want you to waste years of your life and $50-100k getting a masters degree that won't help you.

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Thank you both for your honesty.

I have a lot to think about. I'm probably going to do go to a master's in statistics program this spring (somewhere besides at U of I) and wait to apply for a PhD program next year. I will make it a priority to get research experience!

My whole motivation behind getting into statistics research was to be on the cutting edge of machine learning and data analysis. Which I think really comes from statistics first.

Edited by GeekySarah
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