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Bayesian1701

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Bayesian1701 last won the day on March 25

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About Bayesian1701

  • Rank
    Mocha

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  • Location
    Texas
  • Application Season
    2018 Fall
  • Program
    Statistics PhD

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  1. I am a math major and for those of you, unfamiliar Abstract algebra and Analysis are probably the two hardest undergraduate math courses. A B in abstract algebra isn't that bad of a grade plus it is probably useless (or close to it) for economics. I made a B in Calculus III and a B in Numerical Analysis and still got into great stats PhD programs, and I know there is a difference between stat and econ but I don't think it matters that much. Plus each 3-hour course is worth 2.5% of your final GPA if you take 120 and less if you take more. I don't think adcomms are going to quibble over a few hundredths of a point in GPA.
  2. Bayesian1701

    Fall 2019 PhD Statistics Profile Evaluation

    I am going to chime in here even though I am not as experienced as the three people who applied above. I would drop NYU and Maryland unless you have a special reason to since they are in joint departments and are small. I would apply to 8 to 10 places and maybe do like 1-2 top 10, 2-3 top 20, and 1-2 competitive and prestigious but not highly ranked (Yale, Columbia if you like NYC), and the rest being safer choices. I don’t have many suggestions since I mainly know the southern and Bayesian programs. Speaking from experience on applying too safe, it is possible to regret not applying to top 10 programs.
  3. Bayesian1701

    Gender Discrimination

    I don't normally like to feed trolls, but I felt that this thread needed a woman statistician/mathematician. I am a little late here but I felt like I needed to say something about my sample size of one. I am a female math major. No one has ever told me explicitly that women can't do math. At my undergraduate institution, our department chair is a woman, and we have a large percentage (for math anyway) of female faculty. This does not mean that my experience was easy. It started in middle school, where on more than one occasion I got some weird looks when they announced I won competitions. The disproportionally small number of smart women in STEM in the media didn't help either. In college, when the professor announced what the high score was and it was mine some guys would always ask the other "smart guys" if they got the high score but no one ever thought to ask me. I have gone to office hours and felt like I wasn't viewed by the professor as smart as the guys who would go in before and after me and that I had to prove myself. I felt like I was fighting a constant uphill battle. I didn't consider applying for external PhD programs until I was pushed by some great mentors who saw me not as a woman, but as a great statistician. And in this December I read reports of sexual assaults among female graduate students and young faculty at conferences for my subfield. Yes, I did well in my cycle but I doubt it was *just* because I don't have a Y chromosome. I had to fight to get here, and I am sure your female undergraduate friend had to as well. I have had to endure people like you my entire life, and I probably will for the rest of my life. I would trade any advantage I got because of my gender (which probably wasn't much) in a heartbeat to not have to deal with the disadvantages. You are trivializing the success of others because they did better than you. Like everyone said you don't know that gender was the only reason you didn't do as well as a female applicant. You didn't see the rec letters for the both of you and you didn't apply to the same schools.
  4. Bayesian1701

    Grad. School Supplies?

    I am debating getting a desk for home or spending more money on a nice chair (which is where I usually work). I have the room for a desk. I have never worked on a desk in my life (it's always been the place I put random stuff) and I will have a university provided one in my shared office. Is a home office essential?
  5. Bayesian1701

    HELP! MA Statistiics at Berkeley V Yale

    Yale if your goal is a PhD. Berkeley’s masters program is too applied. Yale isn't a bad program either. If you want Yale and I think your post reflects that, then chose Yale.
  6. Bayesian1701

    MS stats: UWM free vs Duke paid

    UWM all the way. I am a Bayesian and I would make that decision if I was in your shoes. Duke is better for Bayesian but not $165k after interest better. Plus UWM is high enough ranked to probably help you get in a good PhD program in two years.
  7. Bayesian1701

    Best computer to get?

    If you are going to go the windows route I think Lenovo is one of the best brands. If you get their warranty with accidental damage they will cover literally ANYTHING like chargers, cracked screens, batteries. They also have a wide variety of options and lots of sales. I might switch to a Mac though when my current computer dies because windows can get annoying.
  8. Bayesian1701

    Unofficial offer

    Did you get something?
  9. Bayesian1701

    Fall 2018 Statistics Applicant Thread

    All of my offers said sometime on 15th with times ranging from 5 pm to midnight.
  10. @superk60 I am going to assume that your undergraduate institution is a place where a 3.3 is not a bad GPA and math classes are rarely curved, and that your real analysis professor will be like: ”he can handle the math”. But if most people make As in real analysis/probability and you didn't that's going to look bad. That being said your list is probably to reach heavy. To consistently get into top programs (ie get into like 3+) you probably need some combination of luck, a great profile, and a wow factor that makes you unique. Yale and UT Austin may not be highly ranked, but they are both small and still good (Yale being a better program). Your list is mainly (but not completely) top universities (which can be harder to get into even if they aren't highly ranked) and top statistics programs at state schools which means on an as-is basis you might not do well. Safety schools are complicated (some of the lower tier programs are small and/or have funding issues) but you are probably lacking realistic options. I don't really have suggestions on what to drop and what to add because it depends on your preferences (location, program size, research, etc.) but probably fewer places like Yale and Michigan and more places like UConn. A good strategy in general might be (for domestic students) be: 1-4 places you don't think you will get into (group 1), 2-4 places where you expect to get into 25-50% of this group (group 2), and 1-4 places you expect to get into more than 50% of this group (group 3). How you structure your list will be based on how much risk you think you can tolerate. A lot of the programs you are interested are popular (Michigan, Ohio State) enough so that by reading old profiles you can get a vague estimate of what your chances are. But it's probably realistically going to be +/- 20% with the small amount of biased data available. But if you would be happy with applying to all those places and only getting into UConn and maybe one or two other programs, and a slight chance of striking out than go for that list. It's not that you are not a good applicant, its that there are a lot of good applicants.
  11. Bayesian1701

    SOP Advice

    I reread your profile and if that was the semester you took some combination of: Advanced Calculus, Probability Theory, Mathematical Statistics, and other courses it is might be worth a mention because that really stands out as odd and is probably one of the weakest aspects of your profile. Write something up and have a few people look over it. I can look over your SOP when it is finished if you want.
  12. Bayesian1701

    Deadline Predicament - Advice Needed

    I also think you should call Michigan on Monday, and look at visiting Michigan (flights, maybe hotels?) this weekend but don't book anything. I would also wait to ask for an extension at UCI until you are sure you have a funded acceptance at Michigan. I think it might come off as you don't want to go to UCI but I think you do. You should probably tell Michigan (if you haven't already) that you have another offer and they want a response by April 15th so you need to know as soon as possible if they are going to accept you and if you are you want to possibly visit or skype with professors/grad students this week. I would be afraid that Michigan would fall through so I would hold onto that acceptance at UCI until April 15th.
  13. Bayesian1701

    "Let's just TALK about it..." Decision Edition

    I agree with the save up plan others suggested. I have a weird funding package and that is how I am going to fund my summers and my last four years. I vote for A as well, since the money is better, it's closer to home and you like the program better (or least that was my impression). Are you the kind of person that would take advantage of B’s town life? Because if that's not a big factor and the prestige isn't a big difference and you want small class sizes I think you should go with A.
  14. Bayesian1701

    Living in student housing as a grad student

    Update: A condo on the market had its rent reduced and I ended up leasing it. It was in my budget, safe, and 1.5 miles to campus with a bus lane. It's next to an undergraduate heavy complex but I decided that is not a big deal. I would have done with student apartments if the condo didn't appear. For clarification, I would never live in traditional dorms as a grad student (I didn't even live in one for undergrad).
  15. Bayesian1701

    If I knew then what I know now...

    If you are going to visit a program far before results, ask yourself if you can handle a 6-month wait for results and a waitlist/rejection at your first choice. I visited Baylor in October, fell in love and then was waitlisted in March. It was extremely difficult to get waitlisted at a place I had already visited, picked out an apartments, and had potential advisors. I could have saved myself a lot of trouble by not visiting. Also keep you mind open and don't rank places you haven't visited or been accepted too. Chances are you won't get in everywhere so don't waste you time.
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