Regression Models (Coursera)

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.

This course is part of multiple programs

This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:

- Data Science Specialization

- Data Science: Statistics and Machine Learning Specialization

What You Will Learn

- Use regression analysis, least squares and inference

- Understand ANOVA and ANCOVA model cases

- Investigate analysis of residuals and variability

- Describe novel uses of regression models such as scatterplot smoothing

Syllabus

WEEK 1

Least Squares and Linear Regression

This week, we focus on least squares and linear regression.

WEEK 2

Linear Regression & Multivariable Regression

This week, we will work through the remainder of linear regression and then turn to the first part of multivariable regression.

WEEK 3

Multivariable Regression, Residuals, & Diagnostics

This week, we'll build on last week's introduction to multivariable regression with some examples and then cover residuals, diagnostics, variance inflation, and model comparison.

WEEK 4

Week 4: Logistic Regression and Poisson Regression

This week, we will work on generalized linear models, including binary outcomes and Poisson regression.