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School recommendations with my low stats

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Hi everyone! Could you please take a look at my profile and give me some advice about choosing schools for a Ph.D. in Statistics or Biostatistics? Initially, I only planned to earn an MS in Statistics, because I love the subject so much and want to create a better job prospect for myself. However, as involving in research with my professor, I've realized that I like doing research a lot. Some professors of mine actually encouraged me to apply for a Ph.D. But, I am aware that my profile is not that great, so I really don't dream of high-ranking universities. In fact, I would actually feel much happier to be in a program where professors care about students and I can see the work matches my abilities. I just want to get some advice and school recommendations from you all. Please also let me know if you think my application is quite weak for a Ph.D. I would not be sad about that. I just want to have some perspectives to make a better plan for myself. If that is the case, I think I would take more applied classes during my Masters to prepare for the industry. Thank you so much.

Undergrad and Masters Institution: State University in the Bay Area, California. Starting an MS in Statistics in Fall 2019.


Major(s): Statistics (both undergrad and Masters)

Minor: Computer Science
GPA: 3.20 overall, about 3.40 for Math only


Type of Student: Asian immigrant, Male (probably got citizenship by the time applying in Fall 2021)


Lower Division Courses:

Calculus I – AP Credit

Calculus II – B

Calculus III – B

Linear Algebra I – B

Discrete Math – B

Intro Programming – A+

Data Structure – A


Upper-division Courses:

Intro Algorithm – A

Advanced Python – B expected

Financial Math – B

Mathematical Modelling – A

Programming in SAS – B

Applied Statistics I, II – A+

Probability Theory – A

Mathematical Statistics – B+ expected


Graduate Courses: I have taken a few grad classes as an undergrad. I list some classes I am planning to take during my Masters. The program is more like a terminal degree, so more theory-intensive courses in Statistics and Probability are not available.

R Programming – A

Linear Regression – B+

Multivariate Statistics – B+ expected

Time Series – planned

Experimental Design – planned

Computational Statistics – planned

Stochastic Processes – planned

Bayesian Statistics – planned

Classification – planned

I am actually planning to take these two lower-division courses during the first year of my Masters. I kinda avoided them before. But as doing research, I've realized how important they are. I truly want to learn them. In fact, I believe most schools want to see them in the application, and the knowledge of these topics is very necessary during the program.

Introduction to Proofs – see the reason below

Elementary Analysis – see the reason below

GRE General Test:
V: 142
W: 4.0

Programs Applying: Statistics or Biostatistics. I am interested in functional data analysis, i.e. how to use functional data to represent longitudinal or time series data. I am also interested in cluster analysis, and perhaps extend cluster analysis for functional data. Bayesian statistics is also interesting, and can also extend well for functional data, but I just don't have much experience with it now. The application would be in neuroscience, specifically to analyze fMRI, EEG, brain imaging data, etc.

Research Experience: I am currently involved in a one-year research program sponsored by a local company (traditionally, this program is for grad students, but I was lucky enough to get in). We work with cluster analysis and model-based classification for textual data. I will present our research a Data Science & Statistics conference soon. We also have a plan to work on publication later, so that may be a good one. The professor who supervises the research, who is doing active research in cluster analysis, believes that I’ve been working hard, so she gives me the opportunity to help a graduate student with her research this summer (outlier detection and missing data in cluster analysis), and to continue doing side research with her when I start the Masters.

Another professor in my department is doing research in functional data analysis. I did some readings and discussed with her quite a few times. She seems positive about advising me for the Masters' thesis. So, ideally, I would have 2 research opportunities when I start the Masters.

I also volunteer as a research assistant at the VA Palo Alto Healthcare System. Specifically, I am helping them with the stats for their research in brain injury. And they do have plan to publish.

Letters of Recommendation: From the professor with whom I am doing research and my thesis advisor. Possibly one of the researchers at my volunteer workplace.

Considering Programs:  UC Riverside, UC Santa Barbara - both having faculty working in functional data analysis. Also, UC Santa Cruz, UC Irvine - there are faculties having experience in developing Bayesian statistics for functional data and neural data. UC Santa Barbara and UC Irvine are probably more ambitious options for me to be honest. I am particularly considering UC Santa Cruz, because I heard that students here receive good attention from professors (they have a small and new department that has just seperated itself from the School of Engineering lately). The chair of UC Santa Cruz has visited my university recently, and introduced the program. I believe they have good connection with local universities. 



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