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Statistical Modeling

Justifiable, informed decisions have to be made while facing uncertainty, risk, and changing conditions. This module will teach participants rigorous methods for (a) predicting future outcomes based on previous observations and (b) analyzing how those outcomes depend on interacting variables.

  • In Session 1, participants will learn to conduct simple linear regressions, build models with multiple predictors, and interpret the results.
  • In Session 2, participants will learn more advanced modeling techniques (glm and gam approaches) and methods for model evaluation (e.g., goodness of fit tests) and model comparison.
  • In Session 3, participants wil learn how to make predictions based on their models and evaluate the quality and uncertainty of their predictions.

Course Length

  • 9 hours in 3 sessions

Prerequisites