Logistic
Various
Logistic - A book resource
This link may earn us a small commission at no extra cost to you. Affiliate disclosure
More resources on Regression Analysis
Distill.pub
Articles on regression and ML interpretability
Seeing Theory
Interactive regression visualizations, free and practitioner-recommended
Introduction to Statistical Learning
Free book and resources site, top Reddit rec
Linear Regression and Logistic Regression in Python
Master linear & logistic regression in Python with Jose Portilla! Learn key modeling techniques for data analysis.
Statistical Learning
Learn some of the main tools used in statistical modeling and data science. We cover both traditional as well as exciting new methods, and how to use them in R. Course material updated in 2021 for second edition of the course textbook.
Regression Models
Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The course will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing.