We have many variables like the columns in a database, the questions in a survey, etc. Could we build a model to explain the relationships, or even predict the future values?

In this talk, I will introduce the correlation analysis, OLS (ordinary least squares), R formula (an implementation in Python) to build models, covariance types, outliers, common models, and the most important thing: how to build and interpret a model correctly.

Moreover, all the topics will be introduced with massive Python examples!

The notebooks are available on https://github.com/moskytw/statistical-regression-with-python .