[2018 Applicant Profiles and Admission Results for Statistics/Biostatistics]

Undergrad Institution: Large State School (Top 200 USNWR)
Major(s): Mathematics
Minor(s): Statistics
GPA: 3.94

Type of Student: Domestic Male

GRE General Test:
Q: 167 (92%)
V: 165 (96%)
W: 4.0 (60%)

Grad Institution: Same Large State School (Top 200 USNWR) 

Concentration: Mathematical Statistics
GPA: 4.0
 

Programs Applying: Statistics PhD

 

Research Experience: 1 published paper in a low-level journal. Did research every summer as an undergrad. Was a Graduate Research Assistant for multiple projects as a grad student. Presented at local conferences, but nothing major.
Awards/Honors/Recognitions: Many within my school, but nothing outside.
Pertinent Activities or Jobs: Tutored as an undergrad and was a teaching assistant as a grad student.

Letters of Recommendation: My department head, one "well known" prof, and my graduate advisor

Math/Statistics Grades:  A's in graduate level analysis courses and graduate level stats courses

Applying to Where: (Color use here is welcome)
Carnegie Mellon University (CMU) - Statistics PhD / Rejected on 2/9/18

Iowa State University (ISU) - Statistics PhD / Admitted on 2/27/18

Oregon State University (OSU) - Statistics PhD / Rejected on 2/21/18
University of California, Irvine (UCI) - Statistics PhD / Admitted on 2/8/18

[Fall 2018 Statistics Applicant Thread]

@BStat @NumStats UCI visit day is this Friday (March 9). I expect many admitted students are waiting until after the visit to make their decision, as I am. Maybe you are on an unofficial waitlist and some sports will open up in the next few weeks!

[Learning R -- is it worth it?]

The O'Reily 2016 Data Science Salary Survey might have the information you're looking for. You can see the usage of various technologies, as well as salary breakdowns by a bunch of different metrics. With respect R, you can see that it is the second most common technology used by respondents, so it is definitely useful to know outside of school. I think it is also probably the most commonly used language in academia, but, if your school is r-centric, they will almost certainly have some sort of "Introduction to R" class. If you are trying to learn a language *for* grad school, I think you should focus on doing a specific project. An interesting project done in Excel would speak more to your abilities than learning the basics of R/Python/some other language. It would be even better if the project were in a new language.

[Profile Evaluation for Stat PhD/Help Narrow My List]

Undergrad Institution: Large State School
Major(s): Mathematics
Minor(s): Statistics
GPA: 3.95/4.00

Type of Student: Domestic White Male

Grad Institution: Same Large State School

Concentration: Mathematical Statistics (Masters)
GPA: 4.00/4.00

GRE General Test:
Q: 167 (92%)
V: 165 (96%)
W: 4.0 (60%)
 

Programs Applying: Statistics PhD

 

Research Experience: 1 Peer-reviewed publication, 2 summers of research as an undergrad, presented at local/state conferences for undergraduates (won some minor awards), Graduate Research Assistant for one year, which I assume will lead to a publication
Awards/Honors/Recognitions: Phi Kappa Phi Outstanding Scholar, wrote grants which resulted in $5000 in funding for my research, Goldwater Scholarship Nominee, Honors College "Excellence in Research" Award
Pertinent Activities or Jobs: Math tutor when I was an undergrad, Teaching Assistant for one semester, Research Assistant for three semesters in grad school

Letters of Recommendation: Two from professors I have done research with (one young in her career, one a bit older with a good reputation), one from either my department head (who is on my committee) or from another prof on my committee with a good reputation
Any Miscellaneous Points that Might Help: my masters degree (and the qualifying exams I have taken) are the first part of the PhD program at my institution, so I have proven myself in some advanced courses (Measure Theory, Computational Statistics, Asymptotic Statistics)

 

Programs considering:

Personally, I am from the middle of no where in the midwest, and I would ideally like to move to a location with better weather, more interesting terrain, and/or a good music/art scene.
Academically, I am interested in machine learning/computational statistics, and, in particular, like working with text data.  On the side, I am also interested in data visualization. Academia could be in my future, but I would like my program to have good industry ties. If possible, I would prefer a small-medium department to a large one.

 

Very interested:

New York University (NYU) (Data Science PhD) (My favorite program that I have seen. I like the research areas and industry ties, are there other programs like this I could apply to?)

University of California, Los Angeles (UCLA)

University of Texas at Austin (UT Austin)

 

Interested:

University of Washington

Columbia University

Iowa State University (Visualization group is very interesting)

University of California, Irvine

 

Also Interested but, I haven't done a lot of research into these departments
University of Chicago
Duke University

Carnegie Mellon University
University of Michigan

 

Do you think I am competitive at these programs? I would like to remove some of these schools from my list and replace them with some safer schools and ultimately end up with 5-7 to apply to. These are also all fairly larges departments, and I think I am much more suited to a smaller one. Any suggestions are welcome.

[Machine Learning/NLP Profile Evaluatoin]

I'm interested in applying to PhD programs (or funded MS programs) with a focus on machine learning. In particular, I am interested in Natural Language Processing).

I plan to apply this fall and am looking to identify a few reach schools and target schools.

Type of Student: Domestic White Male
Undergraduate Institution: My state's land-grant institution (not particularly known for stats or cs)
Major: Mathematics
Minor: Statistics and a number of CS electives
GPA: 3.95/4.0
Relevant Courses:
A's: Multivariate Calculus, Linear Algebra, Prob & Stats I & II, Computer Science I & II, Data Structures, Predictive Analytics, R Programming, SAS Programming, Forensic Statsitcs (Independent Study), Natural Language Processing (Independent Study), Time Series Analysis, Numerical Analysis, Statistical Computing and Simulation
B's: Real Analysis, Abstract Algebra
Academic Awards/Honors: Goldwater scholarship nomination, Dean's list

GRE: QR: 167 (94%), VR: 165 (95%), AW: 4.0 (56%)

Research Experience:
3 research projects, each presented locally or regionally. One published in a minor journal. One planning to publish in a major journal (probably not accepted by the time of my application).

Letters of Recommendation:
One from a fairly well-known stats professor with whom I have conducted two research projects and one independent study.
One from a brand new stats professor (PhD. from University of Alabama) with whom I have conducted a research project and independent study.
One from math & stats department head whom I know well.

Other considerations: I would like to go to school in a big city, as I have lived in small towns in the midwest most of my life. I manage to find interesting programs at many schools, but could use some help in identifying ones that would be a good fit for my profile.

Thanks for reading!

[Lower PhD program vs MS and reapply?]

Thank you for your input. I really appreciate it. The MS programs that I have gotten into so far are:

-Northern Illinois University (NIU)

-South Dakota State University (SDSU)

-University of Idaho

-my undergrad university

I don't think that they really place anyone into academia but I'm not sure exactly. I know both NIU and SDSU have PhD programs but I believe they are in "Computational Sciences and Statistics" and "Statistics and Applied Probability" respectively but I don't know a lot about them outside that.

 

I'm currently an undergraduate in the math program at SDSU. My advisor has been trying to convince me to do stay here for graduate school. They have made some big hires recently, and the departments is definitely growing. First and second year grad students often travel internationally for conferences, which I am told is not common in bigger departments. As an undergraduate, I don't know a ton about our graduate program, but the few graduate students I have spoken to seem to be happy with their choice to study here. However, if you're looking for Machine Learning, you will not find it here.

 

If you have any more questions about the school or department, let me know.