Profile Evaluation For Fall 2021 (Stats PhD)

[tar.kokor]

Hi all,  I look for the advices about my profile for applying Ph.D. in Statistics in Fall 2021. I am so nervous about the incoming application season since my GRE score in Verbal part is pretty low. I took it many times but my score didn't go up. Currently, I am master student majoring in Statistics in the US University.

Type of Student: International Asian Male
Applying to: Statistics PhD

Undergrad Institution: Top 5 public university in my country
Undergraduate Major: Mathematical Statistics
Undergraduate GPA: 3.8

Graduate Institution: University in the US (Ranked between 11 - 20, according to the USNew)
Graduate GPA: Currently 4.00
Graduate Major: Statistics

Work Experience: I worked as a Data Scientist for 1 year

GRE General Test: Q167 V147 W3.0
I also have a question here that should I retake it?
GRE Mathematics: Not taken

Undergraduate Relevant courses:
Math: Calc I (A), Calc II (A), Calc III (A), Calc IV (A), Fundamental Concepts of Mathematics (Learning about how the proof) (A), Linear Algebra (A), Differential Equation (A), Introduction to Numerical Analysis (Pass; I audited this course)
Stats: Intro to Regression (A), Design of Experiment (A), Categorical Data Analysis (A), Introduction to Multivariate Analysis (A), Probability Theory (B+), Statistical Inference (A), Introduction to Stochastic Process (A), Time Series Analysis (A), Statistical Quality Control (B+), Statistical Simulation (A)
Others: Data Mining (A), Data Science Practicum (A), Operation Research (A), Research Methodology (B+)

** Calc IV at my university is studying about the Sequence and Sequences and series of functions, uniform convergence,  tests for convergence of improper integrals, vector-valued functions of several variables and surface integrals.

Graduate Relevant courses:
Stats: So far, I have taken Regression, Multivariate Analysis, Probability Theory, Statistical Inference, Design of Experiment and Bayesian Modelling (All of them are Master's level)
I think that I will take the Regression, Statistics Inference (Ph.D levels) and some Computational Statistics course.

Research Experience: I have done a research with the Statistics Professor for 8 months about the EM-Algorithm.
Recommendation Letters: 1 of them will be from my professor who I work with and the other 2 will be from the professors who I took his course at get A/A+.  

Planning on Applying to:
Actually, I wish for Standford, UCBerkely, UMich, North Carolina State, Colorado State. However, I'm open to all. I just wonder that what should be some good safety university for me?

Thank you in advance for your suggestions

[DanielWarlock]

- I recommend retaking GRE because your verbal/writing is a bit too low. 

- If your main interest is EM, I recommend applying to Harvard also; there is considerable interest there in Bayesian computation and I think Xiao Li Meng is quite well known as far as EM is concerned. Also Columbia is also a good choice with well-known Bayesian people like David Blei and Andrew Gelman. 

Edited June 24, 2020 by DanielWarlock

[bayessays]

I do not know if your GRE verbal is too low or not. But for an international student, your math background looks pretty weak and doesn't include real analysis, and your research experience is not remarkable for someone coming in with a MS. Honestly, I think you are aiming far too high, and your profile looks weaker than the international students I saw at programs ranked around 40.  I would apply to many more schools like Colorado State but I don't think that is a safe option. Can you take real analysis in your master's program?

[tar.kokor]

Thank you guys for the advise. Yea, I think I will try taking the real analysis course too.