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Bayesian1701 last won the day on March 25 2018

Bayesian1701 had the most liked content!

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About Bayesian1701

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    2018 Fall
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    Statistics PhD

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  1. I'm a third year stats PhD student. My advisor is retiring as soon as I graduate and I'm getting married in June 2021. My fiance doesn't have a lot of job prospects where I attend school. After discussions with my advisor we think it's possible I can graduate in four years even though my program requires 96 credit hours and the average graduation time is five years. It is not unprecedented to graduate in four years but it is rare. I have the advantage that I picked my area of specialization as an undergrad and knew what I wanted my dissertation to look like as a first year. I am not interested in academia, but I should still be able to have a handful of publications in applied stats journals, conference preceedings, and some publications in journals in my field of application. My goal is to become a statistical consultant working in the field of political science and public opinion. By the time I graduate I would have spent three years collaborating with a political science research group doing the exact same work I want to do post-graduation. My disseration would probably not win awards but would include multiple in depth projects presenting new methodological solutions to problems that are common. One thing that makes me a little hesitant is that I graduated undergrad a year early and would be 25 when I got my PhD if all goes according to plan. Graduating early is the best solution for my advisor who wants to retire soon and for my future husband's career. But what I am struggling with is if this is the best solution for me. Does a fifth year as a PhD student add future value for a career or would I be better off graduating early.
  2. I am in this class with 8 other Ph.D. students ranging from 2nd (my year) to 4th years. It's supposed to be a one semester credit hour elective with rotating topics that is pass fail. The point of this is to widen our breadth of knowledge. The syllabus said we needed no background knowledge of the topic and the entire class was in that boat. It was taught by someone from another university none of us had ever had before. He was only on campus to teach the lectures, and we where given the assignments the day before he left. And while I started the homework as quickly as I could I couldn't complete it or ask questions before he left. So stopping by office hours to talk about the assignments is not an option. The syllabus mentioned 12 papers as references, but when the class started this snowballed to an entire textbook (designed for a three hour long semester course), and 5 separate book chapters plus the articles. In other versions of this course there was only a few homework questions, but in this class we had to due a long and theoretical homework assignment and a project that he anticipates taking us three whole days of work. He isn't responding to my emails and I can't go by to see him in person because he is thousands of miles away with a three hour time difference. I haven't found anyone that can figure the homework out and it's due on Tuesday which is also during our spring break. I've spent about probably 30 hours on it so far and now I am completely stuck and can't get any further until he responds. I've contacted the PhD program director and the associate head for teaching. I haven't heard back yet from anyone. And I am currently panicking that I will fail, and that I won't know how to finish the homework in time. And other students agree. Does anyone have any advice or can at least confirm this class is horrible. I'm hoping that either the PhD director or the associate head will step in and intervene but that might be a unreasonable expectation.
  3. Besides linear algebra wouldn't some more math like real analysis and mathematical statistics (undergraduate level) also be helpful? Maybe not necessarily a class, but I think it would be challenging to have just the bare minimum prerequisites and not the optional "prerequisites" like real analysis and probability that would make first-year Ph.D. coursework so much easier.
  4. In most cases, an applied masters program is not going to have any real theory courses. If you don’t take any theoretical stat courses in your program you aren’t going to look (or be) any more prepared for the harder theory PhD courses than you are now.
  5. I’m not familiar with those programs but I can give you some generic advice. Things I considered: 1. Prestige: very similar for Iowa State / Purdue so you could ignore this 2. Degree requirements: length, qualifying/prelim process, required courses 3. Research Areas of faculty 4. Happiness factors including funding, location, weather, etc.
  6. I don’t think Baylor has a MS program really, I was told when I visited last fall that it was there so you could leave with a masters. Another option may be Mizzou for a masters especially if you are interested in funding.
  7. It looks like you have settled on UT but you are sort of asking for permission if that’s a good idea. I say if that’s what you want go for it.
  8. If you think you want to go Bayesian/spatial then go with a place where you have good advisor options in those fields. You might change your mind but you don't want to put yourself in a position where you are struggling to find an advisor to match your interests. I would cross Ohio State off the list. At the end of the day, you can only choose one, and a good program overall may not be a good program for you.
  9. I don't know anything about Biostat programs. Your stat list looks good assuming your biostat list isn't too ambitious.
  10. What is your end goal? Do you want a Ph.D. in statistics or just an applied masters? An applied masters isn't going to help you get into a Ph.D. program. But if an applied masters is your end goal that sounds like a good plan.
  11. I would go ahead and reject offers if you know you aren't interested. You can decide to wait until April 15th and that would be fine. However, I would send out an email asking about your waitlist status in early April. I was in a similar boat and I waited on Duke until late March and is what I would recommend you do unless you know you wouldn't take an offer from Duke. Duke is better than UT Austin, but you may not make it off the waitlist.
  12. UT Austin is basically 100% Bayesian and very heavy on Bayesian nonparametrics. It's fantastic if that's what you want to do but not so much if you aren't sure if you want to go Bayesian. Austin is expensive, but the student usually get high paying tech internships (some in Austin). Texas A&M has a Bayesian lean but has plenty of classical statisticians. Texas A&M is also much larger than the other Texas programs.
  13. I applied to stats programs but I have some visit/decision advice here.
  14. I didn’t see a system that would have let me update fall grades when I applied. If they want it they will ask. Much to my surprise Duke did not ask me about my fall grades during my interview. They probably only care if you are a borderline interview/acceptance.
  15. I would go ahead and apply for the REUs. I agree with the others that the CS courses aren’t that helpful unless you don’t have any experience and they are in languages you are likely to use. Now onto your second question. You will be judged a little harsher with a masters and the masters probably isn’t going to make you graduate with a PhD any faster. The exception is you do extremely well in a top masters program and get great research experience in your first year but that’s pretty rare. You don’t need any research experience so I wouldn’t worry about that. I would apply to PhD if that’s what you think you want. A lot of programs will consider you for a masters if you don’t get into the PhD program. You almost always have the option to drop out with a masters after a few years.
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