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Linear Regression and Modeling
  • Level Foundation
  • Duration 10 hours
  • Course by Duke University
  • Offered by

About

This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.

Modules

Course Overview

    • 1 Videos
    • 2 Readings
Show info about module content

1 Videos

  • Introduction to Statistics with R

2 Readings

  • About Statistics with R Specialization
  • More about Linear Regression and Modeling

Relationship between two numerical variables

    • 4 Videos
    • 1 Readings
Show info about module content

4 Videos

  • Introduction
  • Correlation
  • Residuals
  • Least Squares Line

1 Readings

  • Lesson Learning Objectives

Linear regression with one predictor

    • 4 Videos
    • 1 Readings
Show info about module content

4 Videos

  • Prediction and Extrapolation
  • Conditions for Linear Regression
  • R Squared
  • Regression with Categorical Explanatory Variables

1 Readings

  • Lesson Learning Objectives

Strengthen Your Understanding

    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Week 1 Practice Quiz
  • Week 1 Quiz

1 Readings

  • Week 1 Suggested Readings and Practice

Outliers & Inference for regression

    • 3 Videos
    • 1 Readings
Show info about module content

3 Videos

  • Outliers in Regression
  • Inference for Linear Regression
  • Variability Partitioning

1 Readings

  • Lesson Learning Objectives

Strengthen Your Understanding

    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Week 2 Practice Quiz
  • Week 2 Quiz

1 Readings

  • Week 2 Suggested Readings and Exercises

Learning R

    • 3 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 1 & 2 Lab

3 Readings

  • About Lab Choices
  • Week 1 & 2 Lab Instructions (RStudio)
  • Week 1 & 2 Lab Instructions (RStudio Cloud)

Regression with multiple predictors

    • 4 Videos
    • 1 Readings
Show info about module content

4 Videos

  • Introduction
  • Multiple Predictors
  • Adjusted R Squared
  • Collinearity and Parsimony

1 Readings

  • Lesson Learning Objectives

Inference for multiple regression and model selection

    • 3 Videos
    • 1 Readings
Show info about module content

3 Videos

  • Inference for MLR
  • Model Selection
  • Diagnostics for MLR

1 Readings

  • Lesson Learning Objectives

Strengthen Your Understanding

    • 1 Readings
    • 2 Assignment
Show info about module content

2 Assignment

  • Week 3 Practice Quiz
  • Week 3 Quiz

1 Readings

  • Week 3 Suggested Readings and Exercises

Learning R

    • 2 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 3 Lab

2 Readings

  • Week 3 Lab Instructions (RStudio)
  • Week 3 Lab Instructions (RStudio Cloud)

Data Analysis Project

    • 1 Readings
Show info about module content

1 Readings

  • Project Instructions, Data files, and Checklist

Auto Summary

"Linear Regression and Modeling" is an essential course for those delving into Data Science & AI, presented by Coursera. This foundational course is expertly designed to introduce learners to both simple and multiple linear regression models, which are pivotal in assessing relationships between variables and a continuous response variable. Throughout the course, you'll explore intriguing questions such as the potential correlation between a professor's physical attractiveness and their student evaluation scores, or the ability to predict a child's test score based on their mother's characteristics. Learners will gain a solid understanding of the fundamental theory behind linear regression and apply this knowledge to real-world data examples, enabling them to fit, examine, and utilize regression models effectively. The course leverages the powerful, free statistical software R and RStudio, ensuring hands-on experience with industry-standard tools. Spanning approximately 600 minutes of content, this course is available under the Starter subscription plan, making it accessible to a broad audience. Whether you're a beginner in data analysis or looking to strengthen your statistical modeling skills, this course offers a comprehensive introduction to the principles and applications of linear regression. Join now to start your journey in mastering data relationships and predictive modeling.

Mine Çetinkaya-Rundel
Instructor

Mine Çetinkaya-Rundel