Teaching

2014- present, P8160 Advanced Statistical Computing

As statistical models become increasingly complex, it is often the case that exact or even asymptotic distributions of estimators and test statistics are intractable. With the continuing improvement of processor speed, computationally intensive methods have become invaluable tools for statisticians to use in practice. This course will cover the basic modern statistical computing techniques and how they are applied in a variety of practical situations. Topics to be covered include numerical optimization, random number generation, simulation, Monte Carlo integration, permutation tests, jackknife and bootstrap procedures, Markov chain Monte Carlo methods in Bayesian settings, the EM algorithm, and other selected topics in modern computational statistics.

2013, P6071 Integrate of Science and Practice I & II

Small group sessions that are an integral component of the MPH curriculum—bridge the gap between traditional classroom education and the real-world experience of working as a public health professional.

2004 – 2013, P8116 Design and Analysis of Medical Experiments

This course covers the fundamental principles and techniques of experimental designs in clinical studies.  Topics include reliability of measurement, linear regression analysis, parallel groups design, analysis of variance (ANOVA), multiple comparison, blocking, stratification, analysis of covariance (ANCOVA), repeated measures studies; Latin squares design, crossover study, randomized incomplete block design, and factorial design.

Link to the courseworks@columbia