Building Statistical Models in R: Linear Regression

Coursera Project Network

Build simple and multiple linear regression models

Perform model assessment and interpretation of results

Perform diagnostic checks to test for model assumptions

Clock2 hours
Comment Dots英语(English)

Welcome to this project-based course Building Statistical Models in R: Linear Regression. This is a hands-on project that introduces beginners to the world of statistical modeling. In this project, you will learn the basics of building statistical models in R. We will start this hands-on project by exploring the dataset and creating visualizations for the dataset. By the end of this 2-hour long project, you will understand how to build and interpret the result of simple linear regression models in R. Also, you will learn how to perform model assessments and check for assumptions using diagnostic plots. By extension, you will learn how to build and interpret the result of a multiple linear regression model. Note that you do not need to be a data scientist to be successful in this guided project; just a familiarity with basic statistics and R suffice for this project. If you are not familiar with R and want to learn the basics, start with my previous guided project titled “Getting Started with R”. So, taking this project will give the needed requisite to complete this project on Building Statistical Models in R: Linear Regression. However, if you are comfortable using R, please join me on this wonderful and exciting ride! Let’s get our hands dirty!


  • Statistical Analysis
  • Statistical Model
  • R Programming
  • Ggplot2
  • Linear Regression



  1. Getting Started

  2. Import packages & dataset

  3. Explore the dataset

  4. Data Visualization

  5. Model Building

  6. Model Assessment I

  7. Model Assessment II

  8. Model Prediction

  9. Assumptions Check: Diagnostic Plots

  10. Multiple Regression






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