In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...

A solid coverage of the most important parts of the theory and application of regression models, generalised linear models and the analysis of variance. Analysis of variance models; factors, ...

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 regression takes the logic of the correlation coefficient and extends it to a predictive model of that relationship. Some key advantages of linear regression are that it can be used to predict ...

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 ...

The El Niño-Southern Oscillation (ENSO), the most prominent interannual climate variability signal, has been widely studied ...