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Atypical Applicant: Pathway to Stats PhD?


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Hey all,

So, I'm a pretty atypical applicant. I finished my undergraduate degree in 2019, worked for two years, and then enrolled in a JD (top 3 law school) in 2021. I took a leave of absence from the JD in 2022 due to health problems, and I have since been unemployed and unenrolled while sorting out my health problems. During this time, I have rediscovered my interest in math/statistics and now want to pursue a PhD. My question: given my lack of research experience and connections with statistics professors, is a master's degree the only feasible way for me to remedy these deficiencies and become competitive for PhD programs?

Type: Domestic

Undergraduate Institution: UCLA

Degree: Philosophy

Cumulative GPA: 4.0/4.0

GRE: 168V/167Q

Courses Taken (Grade):

- Real Analysis (A)

- Linear Algebra (A)

- Abstract Linear Algebra (A)

- Analysis of Algorithms (A)

- Probability (A)

- Econometrics (A+) 

Research: Nothing significant. I worked as an RA for a law professor doing some data analysis for a few months.

 

Thanks everyone :)

Edited by moduspwns
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The two posters above are correct. A 4.0 from GPA from a top school UCLA and excellent grades in those math classes definitely make you qualified for a PhD program in Statistics. Research experience is a plus, but not having it won't necessarily hurt your application that much.

There is no need for you to get Masters, but if you have the bandwidth and the funds, you could potentially take a few additional upper division math/stat courses as a non-degree seeking student (for example, you took probability but did you take mathematical statistics?). You could take mathematical statistics, optimization, and another math class at a local university. This might further shore up your application as well, but it isn't strictly necessary.

Your letters of recommendation and your personal statement should emphasize your math ability and your grades in math classes. In addition, you might want to give some explanation for your motivation for wanting to get a PhD in Statistics after exiting law school. At least two of your letters of recommendation should be from math professors who can speak to your ability to succeed in a Statistics PhD program. I have sat on graduate admissions committees, and we really pay attention to math background and letters from professors who can speak to that. Good luck!

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On 3/30/2023 at 2:15 PM, Stat Assistant Professor said:

The two posters above are correct. A 4.0 from GPA from a top school UCLA and excellent grades in those math classes definitely make you qualified for a PhD program in Statistics. Research experience is a plus, but not having it won't necessarily hurt your application that much.

There is no need for you to get Masters, but if you have the bandwidth and the funds, you could potentially take a few additional upper division math/stat courses as a non-degree seeking student (for example, you took probability but did you take mathematical statistics?). You could take mathematical statistics, optimization, and another math class at a local university. This might further shore up your application as well, but it isn't strictly necessary.

Your letters of recommendation and your personal statement should emphasize your math ability and your grades in math classes. In addition, you might want to give some explanation for your motivation for wanting to get a PhD in Statistics after exiting law school. At least two of your letters of recommendation should be from math professors who can speak to your ability to succeed in a Statistics PhD program. I have sat on graduate admissions committees, and we really pay attention to math background and letters from professors who can speak to that. Good luck!

Hi,

Sorry for hijacking the thread, wanted to ask re your comment on recommendations--

I'm a while out of undergrad and won't have letters from undergrad professors. My letters will be from a few PIs and faculty that I've done research with (Psychiatry, Neuroscience world). I know that's suboptimal, even though the letters will be very strong-- do you have any thoughts on this? 

Edited by stats_physics
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2 hours ago, stats_physics said:

Hi,

Sorry for hijacking the thread, wanted to ask re your comment on recommendations--

I'm a while out of undergrad and won't have letters from undergrad professors. My letters will be from a few PIs and faculty that I've done research with (Psychiatry, Neuroscience world). I know that's suboptimal, even though the letters will be very strong-- do you have any thoughts on this? 

Not having undergrad profs is not a big deal - I've had profs, research advisors, even bosses, but they all had PhDs in stats. The bigger concern would be whether your recommenders are qualified to comment on your mathematical ability.

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19 hours ago, stats_physics said:

Hi,

Sorry for hijacking the thread, wanted to ask re your comment on recommendations--

I'm a while out of undergrad and won't have letters from undergrad professors. My letters will be from a few PIs and faculty that I've done research with (Psychiatry, Neuroscience world). I know that's suboptimal, even though the letters will be very strong-- do you have any thoughts on this? 

Letters from research advisors are certainly helpful. LORs don't necessarily need to all be from undergrad professors (some applicants only have letters from professors who taught them in a Masters prorgram and from research supervisors).

Are you saying that you won't have any letters from professors who have taught you in courses, though? That might be a bit unusual -- but possibly not disqualifying, depending on the overall strength of the application. It would be good to have letters that highlight your math/quantitative ability. You could ask your letter writers to highlight your grades in relevant courses. Even just having one generic letter from a prof that confirms you got an A in their course and were ranked in the top 5% of students that semester is often very helpful.

Edited by Stat Assistant Professor
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