Modelling, in statistical terms, is the calculating of parameter values such that we understand the relationship between an independent variable or variables and a dependent variable.

There are four fundamental types of linear models. Fundamental in the sense that understanding these four types, serves as the building blocks for other linear and more generalised models.

In this seminar series, delivered as video tutorials, I explain simple linear regression, one-way analysis of variance, one-way analysis of covariance, and logistic regression.

I use python and the statsmodels package to cover these topics. I visualise the data and the models using the plotly package. The code is written in Jupyter notebooks using Visual Studio Code. The tutorials provides a thorough explanation of linear models, including research questions, null and alternative hypothesis, least squares, sum of squared errors, the F ratio, the coefficients and their statistics, and much more.

The first two video tutorials are already available. View them by following the links below.