AND Mathematical Methods (MA100) or equivalent. It is assumed students have taken at least a first course in linear algebra. A solid coverage of the most important parts of the theory and application ...
id=7745) A solid coverage of the most important parts of the theory and application of regression models, and generalised linear models. Multiple regression and regression diagnostics. Generalised ...
In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...
Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...
In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...
Logistic regression models have one dependent variable and several independent categorical or continuous predictor variables. Unlike standard linear regression models, logistic regression does not ...