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It has been my impression that the GRE Lit Subject test has been slowly falling out of fashion. Despite that, we still have to play the game, don't we? From what I've seen, very few schools require it. Does anyone have a list of the schools that do? When I applied to UVA for my Masters, they accepted me without receiving my score, but since they technically required it, I needed to send my score anyway for administrative purposes. That sent a message to me: "We require this, but it is not that important." That being said, my score was...uh, not very good. I feel compelled to retake it before I apply for PhDs next cycle. But at the same time...maybe my poor score doesn't matter that much? Maybe it's just a formality? We know it's the writing and personal statement that stand out more to committees, but then why should we even bother? What are others' perspective on the importance of the Lit test? What were the best ways to prepare? How long did you study? Did you rely mostly on coursework/background, or additional study materials? Perhaps it would be more beneficial to have a separate thread for listing programs that require it, but I thought I'd give this a shot first.
Hey New gradcafe user and prospective MS applicant for an MS in Operations Research / Statistics / Management Science for Fall 2018. Please evaluate my profile and whether I'm being too ambitious/do I stand a chance here? Key features of my profile - Low undergrad GPA, high quant GRE score, related work ex Here's my profile followed by an initial university shortlist GRE 324 - Q 166 (91st percentile) V 158 (80th percentile) (Might give again to offset low undergrad GPA) TOEFL - Yet to give Undergrad CGPA - 6.3/10 from the National Institute of Technology Warangal in Mechanical Engg - Top 10 India for engineering Work Experience - 3 years 1.5 years - Data Analyst for a Fortune 200 MNC (1 promotion) + 3 good projects - Quantitative Sales/Marketing analytics 1.5 years - Senior Analyst for a Loyalty Card company (jump in designation from previous org) Fair amount of projects on quantitative modelling work Research papers/Publications: None Certifications: 1. SAS certified base programmer 2. SAS certified statistical business analyst: Regression and Modelling 3. Machine Learning from Coursera Recommendations: 1. HOD from work - ex prof at a premier MBA school in India - Strong 2. Team Leader from previous org - Moderate 3. Professor from college - Moderate SOP structure: Considering that my weakest point is my undergrad GPA, I'll bring in a point about how I messed up the first year but post that my gpa has been increasing plus ever since starting work I've been really driven and talk about my projects as proof. Programs I'm looking to apply for: 1. Statistics (with electives from the CS department) 2. Operations Research Not applying for "Analytics" or "Data Science" masters because I feel such programs have breadth but seriously lack depth. Current university shortlist: 1. Columbia 2. University of Chicago 3. UCLA 4. Georgia Tech 5. University of Michigan 6. John Hopkins 7. University of North Carolina at Chapel Hill 8. University of Illinois at Urbana Champaign 9. Duke 10. Cornell Questions: 1. What is my profile like? 2. How would you categorise the above universities considering my profile as Safe, Moderate, Ambitious and reasons for the same? 3. Thoughts on the SOP structure?