bronobo1

Hi everyone, I'm a recent B.S. graduate in desperate need of advice for biostatistics graduate school; I would liked to apply this fall (2020) to PhD/ MS. I'm considering biostatistics, as opposed to statistics, because I like how it has a substantive topic (e.g. biology, genetics, public health), that I really desired from my undergrad. I liked theory, but I was disappointed without a constant substantive topic of application. I'm open to both PhD and MS, but for PhD I'm hesitant since I am unsure of whether I'll like the bio/public health area, but its the best options for my goal: research. For masters, the idea of more loans is scary, but even if I don't like the bio area, I learn more methods with much better job opportunity. The main problem is my GPA. I transferred from community college and had a 3.0 GPA and had an average university GPA, but I took a lot of statistics courses at my university in 6 quarters and 2 summer sessions, so I'm hoping my course load proves I'm competent; I even took 5 technical courses in my last quarter. Here is some background/relevant information: Undergraduate: University of California, Davis Major: Statistics (data science track) GPA: 3.217 (major), 3.207 (overall) Letters of Rec: Have yet to request due to confusion on what to pursue GRE: haven't taken yet. Many are waiving due to COVID-19 Coursework (junior college semester system) Single Variable Calculus I C (fall 2017) Single Variable Calculus II A (spring 2017) Introduction to Linear Algebra A (fall 2017) Multivariable Calculus B (spring 2018) Data structures A (spring 2018) Introduction to Math Proofs A (spring 2018) Coursework (Davis quarter system): Regression Analysis B- (fall 2018) Probability Theory C+ (fall 2018) Analysis of Variance (ANOVA) B- (winter 2019) Math Statistics B (winter 2019) Intro to Data Structures B (winter 2019) Intro to Math Statistics B- (spring 2019) Multivariate Data Analysis B+ (spring 2019) Survey Sampling Theory B- (spring 2019) Applied Linear Algebra B (summer session 2019) Applied Time Series Analysis B+ (fall 2019) Analysis Categorical Data A (fall 2019) Statistical Data Science B+ (fall 2019) Statistical Data Technologies B- (winter 2020) Statistical Learning I B+ (winter 2020) Psychometrics (graduate level) A (winter 2020) Adv Statistical Computing A (spring 2020) Statistical Learning II B (spring 2020) Bayesian Stat Inference A. (spring 2020) Practice in Data Science B+ (spring 2020) Artificial Intelligence, NLP A (spring 2020) Any advice helps...