# Course

## PH 142: Introduction to Probability and Statistics in Biology and Public Health

Course Instructor

Dr. Alan Hubbard

Course Catalog Description

PH 142 is an introduction to statistics and data science, primarily for MPH and undergraduate public health majors, and others interested in public health majors. The course material focuses on the biomedical applications of basic data summarization using the statistical programming language: R, classical problems in probability/statistical distributions (Normal, binomial, Poisson), and statistical inference techniques.

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## PHC242C: Longitudinal Data Analysis

Course Instructor

Alan Hubbard

Course Catalog Description

The course covers the statistical issues surrounding estimation of effects using data on subjects followed through time. The course emphasizes a regression model approach and discusses disease incidence modeling and both continuous outcome data/linear models and longitudinal extensions to nonlinear models (e.g., logistic and Poisson). The primary focus is from the analysis side, but mathematical intuition behind the procedures will also be discussed. The statistical/mathematical material includes some survival analysis...

## PH243A: Targeted Learning

Course Instructor

Mark van der Laan

Course Catalog Description

PH 243A teaches students to construct efficient estimators & obtain robust inference for parameters that utilize data-adaptive estimation strategies (i.e., machine learning). Students perform hands-on implementation of novel estimators using high-dimensional data structures, providing students with a toolbox for analyzing complex longitudinal, observational & randomized control trial data. Students learn & apply the core principles of the Targeted Learning methodology, which generalizes machine learning...

## PH252E: Advanced Topics in Causal Inference

Course Instructor

Alan Hubbard

Course Catalog Description

The course will be conducted as a seminar with readings and discussions on a range of more advanced topics. We will cover case-control designs; longitudinal causal models, identifiability and estimation; direct and indirect effects; dynamic regimes (individualized treatment rules); approaches for diagnosing and responding to violations in the positivity assumption. Additional topics may include stochastic interventions, community-based interventions, and Collaborative-TMLE. There will...