I am an MS student in Data Science and have completed my 1st year. I decided to take Measure Theory because I was very fascinated by it and also wanted to challenge myself with an advanced proof-intensive course. However, I massively underestimated the jump in difficulty from undergraduate to graduate and failed miserably with a D. In retrospect, after completing a triple major as an undergraduate, I was becoming complacent and haughty. This was my first failing grade ever, and it took me a long time to accept it and myself. An ultimately harsh but necessary wake-up call.
Recently, however, my doubts have returned. This summer, I am currently working as a Research Assistant for a project in causal inference, an area that I am very passionate about. I have decided to pursue a Ph.D. to further study it. Based on what I have heard, a B+ in graduate school is a very polite fail; I can't even think what a D stands for. Moreover, I know that many statistics program weigh proof-based courses very heavily. I cannot retake the course in time because (1) a course conflict, (2) I will continue working on this research into the fall, and (3) I honestly don't think I ever use it much now or in the future.
As such, I hope you can give me your honest thoughts about my chance. My undergraduate GPA was 3.83 (BA in Mathematics and Economics & BS in Data Science). My current graduate GPA is 3.50 (All As except the D). My GRE is 166Q, 164V, and 4.5W. I haven't taken the Math GRE because of my summer work, but I can push if needed.
Thank you for reading and sorry for the long post!