Linear regression models the relationship between a dependent and independent variable(s). A linear regression essentially estimates a line of best fit among all variables in the model.

It then discusses the classical linear regression model and commences the discussion of violation of the classical assumptions by discussing the Generalized Linear Regression Model (heteroskedasticity ...

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, ...

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 ...

Their contribution proved to be a very useful generalisation of classical normal ... logistic regression appropriate for categorical responses; and log-linear models appropriate for discrete ...

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 ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...