## Course: Regression Models

# Lecture Materials

Except where otherwise indicated, this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License . Your use of this material constitutes acceptance of that license and the conditions of use of materials on this site.

The links below are to the materials used during the lecture portions of this course. To sign up to take the course online, please visit the Johns Hopkins Data Science Specialization.

## Module 1

## » Lecture 1.1: Introduction to Regression

## » Lecture 1.2: Basic Notation and Background

## » Lecture 1.3: Linear Least Squares

## » Lecture 1.4: Regression to the Mean

## » Lecture 1.5: Statistical Linear Regression Models

## » Lecture 1.6: Residuals

## » Lecture 1.7: Inference in Regression

## Module 2

## » Lecture 2.1: Multivariate Regression

## » Lecture 2.2: Multivariable Regression Example

## » Lecture 2.3: Multivariable Simulation Exercises

## » Lecture 2.4: Residuals

## » Lecture 2.5: Some thoughts on model selection

## Module 3

## » Lecture 3.1: Generalized Linear Models

## » Lecture 3.2: Binary Data GLMs

## » Lecture 3.3: Poisson Regression

## » Lecture 3.4: Fitting Functions