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I'm European and have been admitted to three master programs at good/great universities in other continental european countries. I have to make my decision soon and I feel like I have a good picture of the fit of the programmes and their faculty to my research interests,of student life in these places, and of the overall reputation of the university. However, as a foreign student and someone with no substantial network within my field yet, I have a very hard time assessing how these universities are known in my field and what their strengths and weaknesses are in it. Sorry if this is a basic question, but how did/do you assess this when you can't ask people with more experience? This feels like the missing piece in my decision puzzle, but is also of general interest to me. Any advice/experiences would be appreciated.
Hi, I correlated all my study variables, and some of the demographic variables, with each other, to see if there were any significant associations. I found significant correlations between some study variables with demographic variables. For example, let's say I analyzed which type of candy participants like eating the most; and the amount of candy XY eaten correlated with participant's educational status. This would seem like a "spurious" association, as in there would be no obvious explanation why participant's education should be associated to how much of candy XY they eat. My questions: 1) Is it common to to this sort of preliminary correlational analyses to explore associations between variables? 2) Should I report significant correlations, even if they are not part of my study questions/hypotheses? 3) If yes, should I mention these significant correlations as well in my discussion? Or can I simply report them in my results part, and them not mention them anymore in the discussion? Thank you in advance !
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?