Simple Linear Regression in R

4 hours of instruction

Regression is a machine learning technique that can be used to model and predict the relationship between variables, features and a continuous numerical target. In this course, learners will identify use cases for simple linear regression, focusing on the relationship between two variables only. Students will build, evaluate, and interpret a simple linear regression model in R, with an emphasis on checking the model for explanatory and predictive power.

OBJECTIVES

1. Identify opportunities and use cases for regression models
2. Build and evaluate simple linear regression models
3. Assess statistical significance and validate models for explanatory power and bias

PREREQUISITES

Learners must be comfortable using R to manipulate data and must know how to create basic visualizations.

SYLLABUS & TOPICS COVERED

1. Simple Linear Regression
   • Regression use cases
   • Simple linear regression in a nutshell
   • Implement simple linear regression on a dataset

SOFTWARE REQUIREMENTS

You will have access to an R-based Posit Cloud environment for this course. No additional download or installation is required.