Regression Models

Coursera MOOC / Non-credit USD 49
Enroll now →
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'll learn

  • understand the fundamentals of regression analysis
  • apply least squares method for inference
  • learn about special cases of regression like ANOVA and ANCOVA
  • analyze residuals and variability
  • explore modern techniques in model selection

Skills you'll gain

Related courses

Course details are provided by the platform and may change — always confirm on the provider's site. Links may be affiliate links.