I have a PhD in Statistics (Berkeley), MS in Finance (Berkeley) and BS in Mathematics (Europe). I've been tutoring statistics, stochastic processes, optimization, machine learning, finance and actuarial mathematics for 11 years. I have helped high school students, undergraduate students and graduate students to improve performance on their assignments and exams. I have helped researchers and business professionals with high-level data-driven projects.
My teaching style tends to adapt to...
I have a PhD in Statistics (Berkeley), MS in Finance (Berkeley) and BS in Mathematics (Europe). I've been tutoring statistics, stochastic processes, optimization, machine learning, finance and actuarial mathematics for 11 years. I have helped high school students, undergraduate students and graduate students to improve performance on their assignments and exams. I have helped researchers and business professionals with high-level data-driven projects.
My teaching style tends to adapt to the needs of the student. Some students need structured exposition: block by block, solution by solution. Some students need an informal discussion, connecting various results and ideas in different fields. Some students need me to tell them how to structure the study program and which courses to take over the next 1.5 years. Some clients (often business professionals) just need the data analysis done, as thoroughly as possible, and then they learn from my results and my conclusions. Therefore, the teaching format is flexible. One thing which is uniformly true: the cost of the service increases with the level of work. For example, requesting implementation of a robust pattern recognition system would require a different budget compared to studying Poisson processes or option pricing on the graduate level.
I work in the following packages: R (RStudio), Matlab, Python, Stata, SPSS, JMP, Microsoft Excel, Minitab, EViews, SAS. Depending on student’s needs, I can exploit standard libraries or build my own, customized code. Over the years I have seen some packages improve substantially and I use them more and more often. R and Stata are notable examples. Python is becoming more popular because of its memory management and CPU management style.
My broad statistical training allows me to expose professionals in one applied field to methods most popular in another applied field. For example, some aspiring biostatisticians and medical professionals (not all) come to me with quite narrow data analysis training, centered around ANOV