Linear regression is a statistical method used to model the relationship between ... In simple terms: The result is an equation you can use to estimate future outcomes based on known data.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way ...

Linear and nonlinear regression are similar in that both track a particular response from a set of variables. As the ...

Ordinary regression analysis is based on several statistical assumptions. One key assumption is that the errors are independent of each other. However, with time series data, the ordinary regression ...

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 ...

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

and linear statistical models in particular. 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 ...