I’m looking to get into mid tier MS-Applied statistics grad schools(ie Rutgers or similiar). I’m going to be working full time and going to school part time. I have strong industry experience, specifically industry experience in a concentration that is offered ( quality).
I’ve been out of undergrad for a long time (10 years). I’ll have mostly letters of recommendations from industry. My company will be paying for the majority of the tuition(and I'll be paying the rest).
I have a low GPA(2.46) and I realize that this most likely is not going to be good enough to get into a masters program(but of course let me know if you don’t think that’s the case) and I’ll need to improve my application.
I was considering one of the following online at a school such as UC Berkely extension school or similar:,
-Retaking 2 of the 4(Calc 1,2,3(multi-variate) and linear algebra) pre-requisite math courses and demonstrating better performance. I was thinking of taking Calc 2 and 3, do you think this is the correct choice? If it matters I received a B in my undergrad applied statistics course. If not which of those 4 do you suggest
-Taking the GRE Math Subject test which covers some of the material. The application page says GRE general is required for MS(doesn’t mention anything about the GRE Math subject test). For the PHD admission it says GRE Math Subject Test is strongly recommended. What kind of score do you think i need to get to make this one viable?
Assuming successful completion of one of the two, what do people think my chances are? Which is more likely to be successful?
