• Understand the concept of regression
• Build logistic regression models
• Interpret regression results
• Build linear regression models
• Build count models
• Visualize the results

This course explores three basic regressions—linear, logistic, and count model. Starting with linear regressions, you’ll first understand the difference between simple and multiple linear regressions and explore different types of variables, including binary, categorical, and quadratic. Once you’ve got to grips with the fundamentals, you’ll apply what you’ve learned to solve a case study. As you advance, you’ll explore logistic regression models and cover variables, non-linearity tests, prediction, and model fit. Finally, you’ll get well-versed with count model regression.

By the end of the course, you’ll be equipped with the knowledge you need to investigate correlations between multiple variables using regression models.

All the codes and supporting files for this course will be available at- https://github.com/PacktPublishing/Understanding-Regression-Techniques

• Understand the normality and independence of residuals
• Explore both graphical and non-graphical tests for non-linearity in logistic regression models
• Get to grips with count tables, their risk, and incidence rate ratio