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PhD Stat Prereqs


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I am considering returning to school to pursue PhD in the near future. However, I did not take any math classes (minus intro to statistics and precalc credit) so I will need to take prereq classes. My question is, how important is getting the prereq classes completed at 4-year university vs. community college? Also are online courses considered negative vs. in-person courses? Thanks!

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Community college courses might be acceptable for obtaining the prerequisites, but not necessarily for getting the best letters of recommendation. For PhD admissions, it's better if your letters come from people who hold PhDs that can speak to your "research potential." You'd have a greater chance of getting such letters from professors at 4-year colleges/universities. That said, for PhD admissions, you probably shouldn't ask instructors of Calculus I-III or Linear Algebra for LOR's anyway (Masters admissions are a different story), unless you took more upper division classes with the same instructors. 

Since you don't have any of the math prereqs, you could take Calc I-III and Linear Algebra at community college. That would be enough for you to get into many Masters programs in Statistics. But then in order to be competitive for PhD programs in Statistics, you need at least a few upper division math classes as well, and it would be better to take those upper division classes at a 4-year school.

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As long as you can secure strong letters of recommendation from your online professors, it should be okay. In order for them to say more than just "so-and-so was a good student who got an A in my class," you may need to interact with them somewhat more. As long as you can make sure you get sufficient interaction with them and get to know them well enough for them to write you a strong letter, I don't see any problem with online classes. (Fact is, as a result of the pandemic, students taking upper division classes completely remotely has been the norm rather than the exception).

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On 8/24/2021 at 11:09 AM, Stat Assistant Professor said:

As long as you can secure strong letters of recommendation from your online professors, it should be okay. In order for them to say more than just "so-and-so was a good student who got an A in my class," you may need to interact with them somewhat more. As long as you can make sure you get sufficient interaction with them and get to know them well enough for them to write you a strong letter, I don't see any problem with online classes. (Fact is, as a result of the pandemic, students taking upper division classes completely remotely has been the norm rather than the exception).

Thank you for the response. Are there any "expiration date" to prereq courses? As in, is it less competitive to have prereqs that are more than certain number of years old? I know that for some professional schools strongly prefer (or even require) prereq classes that are within 5 years of marticulation, but I haven't been able to find any information on whether or not PhD programs have a such preference.

 

Also, do biostat PhD programs have same prerequisites as statistics PhD?

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To get into a Biostat PhD program ranked below the top ~10 Biostat programs, the math requirements are lighter than for Statistics PhD programs. In some cases, you only need Calculus I-III and Linear Algebra. Even for Biostat, having real analysis helps though, as do a few other upper division stat/math classes (e.g. the undergrad-level probability and statistics sequence). The more elite Biostat programs might favor deeper math backgrounds.

As for "expiration date," I don't think there is such a thing. There are people with PhDs in Statistics who began their studies a decade (or more) after graduating with their Bachelor's. It doesn't really matter when you took the prerequisites as long you have them. However, if you have been out of school for that long, you would have forgotten a lot of details from college-level math and would need to spend a bit of time reviewing Calculus and Linear Algebra before starting the PhD.

Edited by Stat Assistant Professor
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