Regression Models

About this course

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.

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