lynntoujours

I was in a similar situation last year when I applied: Econ major with high GPA and insufficient math background. But I did have mathematical probability and two more advanced econometrics courses. And I got into Berkeley and Duke, certainly not as great as other applicants with stellar profiles, but acceptable. My suggestion would be: if you work a lot with data in your consulting job, maybe it is better to ask your supervisor to write a letter for you (instead of Calc professor)? If possible, take one or two summer courses, multivariable calculus and mathematical probability are all good choices. The admission committee is searching for your grades of these courses on your transcript. Also, maybe you can take GRE Math Subject to make up the light background?

Hey just wanna let you know I chose UCB at last. Duke has better program, but it's all about location, location, location. lol.

I got accepted to both UCB and Duke so probably I can offer you more info on these two schools. I went to Duke's Open House event last weekend and enjoyed it a lot. All the professors are very nice and approachable, and it seems like the department cares a lot about the MSS program, which is kinda unusual comparing to other schools. TA and RA opportunities are plenty, so is opportunity to work with Duke Medical center on health-related projects (the director mentions year-long internship, it seems like the medical center really needs people who can analyze large datasets). The department is very Bayesian-focused, but I don't think it means a lot for employers. The curriculum strikes a great balance between theoretical and applied sides. And of course, two-year duration is always better than one-year. However, from what the MSS students told me, firms in RTP hire more students from Chapel Hill and NC State than Duke, partially because Duke is trying to be 'national' and 'international'. Given its location, it is hard to go 'national'. So that has put Duke in a very awkward position. Jobs in Bay Area are certainly possible, but you need to work very hard by yourself. Staying in RTP is relatively easy (if not guaranteed), so most people use it as a back-up plan. For UCB, it is possible to stay for a third semester if you become a TA for the 2nd and 3rd semester. The department is more theoretical. Opportunities in Bay Area are plenty, because of its location and alum network. But personally I don't think the department puts much emphasis on the MA program, especially when comparing with Duke. I chose UCB at last. Although I believe going to Duke would be a MUCH MORE ENJOYABLE experience, and I like the program very much, I have succumbed to UCB's location and stronger alum network. Hope it helps.

Thank you for your advice! Duke has done a great job in posting placement results, if only Berkeley can do the same!

This may be the most difficult decision in my life. Have been tortured by this for over a week now. I am planning to go to Duke's Open House event next week, hope that could help. If you have any new thoughts about these two programs, could you please post them here so that we could discuss? I will surely do the same. Thank you!

Thank you for your advice! Because I don't have a strong mathematical and statistics background, I really want to gain a systematic understanding of statistics in masters program. Two-year Duke program seems to be better in this aspect, though very theoretical. However, given that I want to work in data science after graduation, Berkeley (strength in CS, location, reputation, more alums in this industry) may help me more with job-search. To become a data scientist, do you think I should focus more on machine learning and programming (Berkeley) or lay a systematic, solid foundation (Duke) first? Thank you so much for your help! I deeply appreciate it.

I fortunately got accepted into statistics master's programs at UC Berkeley, Duke, Yale and Analytics MS at USF. My plan is to work in data science for 2-3 years after the masters and then apply for Statistics PhD. That being said, I guess my future research interest would be in data science/machine learning, etc. After PhD, I will return to industry and work as a data scientist. Based on my plan, which program do you think I should choose? UCB's location is wonderful, but it is only a one-year program. I am an economics major, instead of math or statistics. So to prepare for PhD application, actually I need to take a lot of classes in math and statistics. I don't know if one year is enough. Plus, if I am focusing on getting good grades at Berkeley, I am afraid I won't have enough time to apply for full-time jobs and prepare for tech interviews. After all, my primary goal after masters is to work in data science. Duke's program is two-year, and if I do extremely well, there is a high chance that I can get into its PhD. So PhD preparation-wise, I think it would be a good choice. But on the other hand, speaking of job opportunities, I don't think Durham NC could compete with Silicon Valley. After all, I need to secure a job after graduation. Should I even consider Yale or USF analytics? Any suggestions will help. Thank you so much!

Thank you! It is very helpful! I will just ignore its brand and location then.

The efficiency of Columbia Stats masters admission is unbelievable. Got accepted two weeks after I submitted the application. I heard some negative comments about this program. Between Columbia stats masters and Yale stats masters, could anyone give me some suggestions on which one is better? Yale has a very small department, I guess that explains a lot about their relatively lower ranking. I visited the department last week and liked it a lot. Feels like it would be a better choice than Columbia. Any suggestions please?

The results of these 3 programs are posted???

You can try Columbia's MA Statistics Program (ranked 20ish I believe). No kidding, but their deadline is in April!

Gotcha. Thank you!

Thanks! have you heard anything about UCBerkeley stats masters?

Excuse me, are you talking about UC Berkeley masters or PhD?

Yes, the result was out this Monday.