Hello! My name is Cherie. I hold a B.S. in Statistics, and a Master degree in Biostatistics. I specialize in guiding high school and college students through subjects in data science, with a strong focus on statistical methods.
My official tutoring experience included working as a Teaching Assistant for Foundations of statistics in college. Over my more than 20 sessions of teaching, I thoroughly enjoyed helping students become more confident with statistics through leading small group...
Hello! My name is Cherie. I hold a B.S. in Statistics, and a Master degree in Biostatistics. I specialize in guiding high school and college students through subjects in data science, with a strong focus on statistical methods.
My official tutoring experience included working as a Teaching Assistant for Foundations of statistics in college. Over my more than 20 sessions of teaching, I thoroughly enjoyed helping students become more confident with statistics through leading small group review sessions and providing one-on-one support for homework and test preparation. I subsequently worked on analysis of drug safety and efficacy in Pharma, and coached junior team members on statistical methodologies. I also worked in corporate digital marketing in the past few years where I applied machine learning in refining corporate marketing strategies.
Choosing me as a tutor means working with someone who is knowledgeable about foundational topics as well as flexible in using versatile modeling technologies in healthcare and business. I supplement explanations to abstract concepts with real-world examples and contexts, with the goal of building confidence for problem-solving.
I offer help across a wide range of topics, including but not limited to the following areas:
Statistical tests and procedures: when and how to apply different methods
Descriptive statistics: Mean, Median, variance, Standard Deviation, Exploratory data analysis
Probability theories: Combinatorics, distributions, conditional probability, Bayes’ Theorems
Inferential Statistics: Hypothesis testing, confidence intervals, chi-square tests, ANOVA,Non-parametric tests, sampling methods and estimation, power and sample size calculation
Survival Analysis: cox-proportional hazard models, Kaplan-Meier curves
Statistical programming in Python: PANDAS, NUMPY, visualization, modeling packages
