Advice on Graduate Biostatistics, Low GPA

[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)

1. Single Variable Calculus I C (fall 2017)
2. Single Variable Calculus II A (spring 2017)
3. Introduction to Linear Algebra A (fall 2017)
4. Multivariable Calculus B (spring 2018)
5. Data structures A (spring 2018)
6. Introduction to Math Proofs A (spring 2018)

Coursework (Davis quarter system):

1. Regression Analysis B- (fall 2018)
2. Probability Theory C+  (fall 2018)
3. Analysis of Variance (ANOVA) B-  (winter 2019)
4. Math Statistics B  (winter 2019)
5. Intro to Data Structures B  (winter 2019)
6.  Intro to Math Statistics B-  (spring 2019)
7. Multivariate Data Analysis B+  (spring 2019)
8. Survey Sampling Theory B-  (spring 2019)
9. Applied Linear Algebra B  (summer session 2019)
10. Applied Time Series Analysis B+  (fall 2019)
11. Analysis Categorical Data A  (fall 2019)
12.  Statistical Data Science B+  (fall 2019)
13.  Statistical Data Technologies B-  (winter 2020)
14.  Statistical Learning I B+  (winter 2020)
15.  Psychometrics (graduate level) A (winter 2020)
16.  Adv Statistical Computing A  (spring 2020)
17.  Statistical Learning II B  (spring 2020)
18. Bayesian Stat Inference A. (spring 2020) 
19. Practice in Data Science B+  (spring 2020)
20. Artificial Intelligence, NLP  A (spring 2020)

Any advice helps... 

Edited September 4, 2020 by bronobo1
typo