Linear regression is graphically depicted using a straight line; the slope defines how the change in one variable impacts a change in the other. The y-intercept of a linear regression relationship ...

We call these “slope values”, regression coefficients or beta coefficients. The main distinction between different types of regression model is that they are used for different types of outcome (eg, ...

In this module, we will learn how to fit linear regression models with least squares. We will also study the properties of least squares, and describe some goodness of fit metrics for linear ...

It is not desirable to use ordinary regression analysis for time series data since the assumptions on which the classical linear regression model is based will usually be violated. Violation of the ...

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, ...

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 of regression models, and generalised linear ...

Linear regression is graphically depicted using a straight line; the slope defines how the change in one variable impacts a change in the other. The y-intercept of a linear regression relationship ...