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Linear Regression and Modeling

4.8 Filled star Filled star Filled star Filled star Half star
Based on 1,770 ratings
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Mine Çetinkaya-Rundel

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.

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Syllabus

About Linear Regression and Modeling
This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Linear Regression and Modeling. Please take several minutes to browse them through. Thanks for joining us in this course!
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Develops fundamental theory behind linear regression, which is core to data analysis
Emphasizes the application of learned concepts through data examples
Utilizes the free and widely used statistical software R and RStudio
Covers a comprehensive range of topics, from basic to advanced concepts in linear regression
Provides a strong foundation for further study in statistics and data analysis
Taught by Mine Çetinkaya-Rundel, an experienced instructor in the field

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Linear Regression and Modeling with these activities:
Watch tutorials on linear regression with R
Watching tutorials will provide you with additional instruction and examples of how to use linear regression in R.
Browse courses on Linear Regression
Show steps
  • Search for tutorials on linear regression with R on YouTube or other video platforms.
  • Watch several tutorials to learn different approaches and techniques.
Read 'Linear Models with R'
Reading this book will introduce you to the fundamentals of linear regression and provide a solid foundation for the course.
View Linear Models with Python (Chapman & Hall/CRC... on Amazon
Show steps
  • Read chapters 1-3 to understand the basics of linear regression.
  • Work through the exercises in chapters 1-3 to practice your understanding.
Running practice files in R
Running practice files in R will help you become more proficient in using the software and applying linear regression techniques.
Browse courses on Linear Regression
Show steps
  • Download the practice files from the course website.
  • Open RStudio and load the practice files.
  • Run the practice files and check your output against the expected results.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Form a study group with other students
Forming a study group will allow you to discuss the material with other students and get different perspectives.
Browse courses on Linear Regression
Show steps
  • Find a few other students who are taking the course.
  • Meet regularly to discuss the material, work on problems, and quiz each other.
Practice multiple linear regression problems
Practicing multiple linear regression problems will help you develop your skills in using this technique.
Browse courses on Multiple Linear Regression
Show steps
  • Find a dataset with multiple independent variables.
  • Fit a multiple linear regression model to the dataset using R.
  • Interpret the results of the model.
Answer questions in the course discussion forum
Answering questions in the discussion forum will help you reinforce your understanding of the material and help other students in the course.
Browse courses on Linear Regression
Show steps
  • Read through the discussion forum and identify questions that you can answer.
  • Write thoughtful and informative responses to the questions.
Final project: Analyze a dataset using linear regression
The final project will allow you to apply your knowledge of linear regression to a real-world dataset and demonstrate your understanding of the concepts covered in the course.
Browse courses on Linear Regression
Show steps
  • Choose a dataset that is relevant to your interests.
  • Explore the dataset and identify potential relationships between variables.
  • Fit a linear regression model to the dataset.
  • Interpret the results of the model and draw conclusions.
  • Write a report summarizing your findings.

Career center

Learners who complete Linear Regression and Modeling will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use statistical methods to extract meaning from data. They use their findings to help organizations make informed decisions. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Data Analyst.
See salaries and explore the career path for Data Analyst
Financial Analyst
Financial Analysts use statistical and financial models to evaluate investments. They use their findings to make recommendations to clients. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Financial Analyst.
See salaries and explore the career path for Financial Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They use their findings to improve efficiency and effectiveness. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as an Operations Research Analyst.
See salaries and explore the career path for Operations Research Analyst
Actuary
Actuaries use mathematical and statistical models to assess risk. They use their findings to make recommendations to clients about how to manage their risks. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as an Actuary.
See salaries and explore the career path for Actuary
Biostatistician
Biostatisticians use statistical methods to analyze data in the field of biology. They use their findings to help scientists understand the causes and treatments of diseases. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Biostatistician.
See salaries and explore the career path for Biostatistician
Statistician
Statisticians use statistical methods to analyze data in a variety of fields. They use their findings to help businesses, governments, and other organizations make informed decisions. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Statistician.
See salaries and explore the career path for Statistician
Data Scientist
Data Scientists use statistical and machine learning methods to extract meaning from data. They use their findings to help organizations make informed decisions. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Data Scientist.
See salaries and explore the career path for Data Scientist
Market Researcher
Market Researchers use statistical methods to collect and analyze data about consumers. They use their findings to help businesses develop and market their products and services. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Market Researcher.
See salaries and explore the career path for Market Researcher
Economist
Economists use statistical and economic models to analyze economic data. They use their findings to make recommendations to governments and businesses about economic policy. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as an Economist.
See salaries and explore the career path for Economist
Quantitative Analyst
Quantitative Analysts use statistical and mathematical models to analyze financial data. They use their findings to make recommendations to clients about how to invest their money. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Quantitative Analyst.
See salaries and explore the career path for Quantitative Analyst
Software Engineer
Software Engineers design, develop, and maintain software applications. They use statistical methods to analyze data and improve the performance of their applications. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Software Engineer.
See salaries and explore the career path for Software Engineer
Business Analyst
Business Analysts use statistical and business methods to analyze data and identify opportunities for improvement. They use their findings to help businesses make informed decisions. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Business Analyst.
See salaries and explore the career path for Business Analyst
Consultant
Consultants use statistical and business methods to help businesses solve problems and improve their performance. They use their findings to make recommendations to clients about how to improve their operations. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Consultant.
See salaries and explore the career path for Consultant
Marketing Manager
Marketing Managers use statistical and marketing methods to develop and implement marketing campaigns. They use their findings to track the success of their campaigns and make improvements. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Marketing Manager.
See salaries and explore the career path for Marketing Manager
Product Manager
Product Managers use statistical and product management methods to develop and manage products. They use their findings to make decisions about product features, pricing, and marketing. This course introduces the fundamentals of linear regression, a statistical technique that can be used to model the relationship between two or more variables. By taking this course, you will gain the skills necessary to analyze data and draw meaningful conclusions. This course is a valuable resource for anyone who wants to enter or advance their career as a Product Manager.
See salaries and explore the career path for Product Manager

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Linear Regression and Modeling .
Cover image
An Introduction to Statistical Learning
Save
Provides a comprehensive overview of statistical learning methods, including linear regression. It valuable resource for anyone who wants to learn more about the theory and practice of statistical modeling.
An Introduction to Statistical Learning
Paperback
Check
An Introduction to Statistical Learning
Kindle Edition
Check
Cover image
Linear Models with Python
Save
Provides a practical guide to fitting linear models in R. It valuable resource for anyone who wants to use R for data analysis.
Linear Models with Python (Chapman & Hall/CRC Texts...
Hardcover
$$$
Linear Models with Python (Chapman & Hall/CRC Texts...
Kindle Edition
$$$
Cover image
Regression Modeling with Actuarial and Financial...
Save
Provides an introduction to regression modeling with a focus on actuarial and financial applications. It valuable resource for anyone who wants to learn more about the use of regression models in these fields.
Regression Modeling with Actuarial and Financial...
Paperback
$$
Regression Modeling with Actuarial and Financial...
Kindle Edition
$$$
Cover image
Generalized Linear Models, Second Edition
Save
Provides a comprehensive overview of generalized linear models. It valuable resource for anyone who wants to learn more about the theory and practice of generalized linear modeling.
Generalized Linear Models with Random Effects:...
Kindle Edition
$$$
Cover image
Presenting Medical Statistics from Proposal to...
Save
Provides a practical guide to statistical methods used in medical research. It valuable resource for anyone who wants to learn more about the use of statistical methods in this field.
Presenting Medical Statistics from Proposal to...
Paperback
$$$
Presenting Medical Statistics from Proposal to...
Kindle Edition
$$
Cover image
An R Companion to Applied Regression
Save
Provides a practical guide to fitting linear models. It valuable resource for anyone who wants to learn more about the theory and practice of linear modeling.
An R Companion to Applied Regression
Paperback
$$$
An R Companion to Applied Regression
Paperback
$$
An R Companion to Applied Regression by John Fox...
Paperback Bunko
$$$
An R Companion to Applied Regression
Kindle Edition
$$$
Cover image
Linear Regression Analysis
Save
Provides a comprehensive overview of linear regression analysis. It valuable resource for anyone who wants to learn more about the theory and practice of linear regression.
Linear Regression Analysis
Hardcover
$$$$
Cover image
Regression Analysis by Example Using R
Save
Provides a practical guide to regression analysis. It valuable resource for anyone who wants to learn more about the theory and practice of regression analysis.
Regression Analysis By Example Using R (Wiley...
Hardcover
$$$$
Regression Analysis By Example Using R (Wiley...
Kindle Edition
$$$$
Cover image
The Elements of Statistical Learning
Save
Provides a comprehensive overview of statistical learning methods. It valuable resource for anyone who wants to learn more about the theory and practice of statistical modeling.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Cover image
Machine Learning for Hackers
Save
Provides a practical guide to machine learning. It valuable resource for anyone who wants to learn more about the theory and practice of machine learning.
Machine Learning for Hackers: Case Studies and...
Paperback
$$
Machine Learning for Hackers: Case Studies and...
Kindle Edition
$$
Cover image
Data Science for Business
Save
Provides a practical guide to data science. It valuable resource for anyone who wants to learn more about the theory and practice of data science.
Data Science for Business: What You Need to Know...
Paperback
$$
Data Science for Business: What You Need to Know...
Kindle Edition
$$
Cover image
Hands-On Machine Learning with R
Save
Provides a practical guide to machine learning with R. It valuable resource for anyone who wants to learn more about the theory and practice of machine learning with R.
Hands-On Machine Learning with R (Chapman &...
Hardcover
$$$
Hands-On Machine Learning with R (Chapman &...
Kindle Edition
$$$
Cover image
Reinforcement Learning, second edition
Save
Provides a comprehensive overview of reinforcement learning. It valuable resource for anyone who wants to learn more about the theory and practice of reinforcement learning.
Reinforcement Learning, second edition: An...
Hardcover
$$$
Reinforcement Learning, second edition: An...
Kindle Edition
$$$
Cover image
Bayesian Data Analysis, Third Edition
Save
Provides a comprehensive overview of Bayesian data analysis. It valuable resource for anyone who wants to learn more about the theory and practice of Bayesian data analysis.
Bayesian Data Analysis (Chapman & Hall/CRC Texts in...
Kindle Edition
$$$$
Cover image
Causal Inference in Statistics
Save
Provides a comprehensive overview of causal inference in statistics. It valuable resource for anyone who wants to learn more about the theory and practice of causal inference in statistics.
Causal Inference in Statistics - A Primer
Paperback
$$
Causal Inference in Statistics: A Primer
Kindle Edition
$$

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Course image
Rating
4.8 Filled star Filled star Filled star Filled star Half star
Effort
Approx. 10 hours
Level
Introductory
Via
Coursera
Institution
Duke University
Instructor
Mine Çetinkaya-Rundel
Language
English
Transcripts
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Linear Regression and Modeling belongs to the following collections:
  1. Statistics with R
  2. Data Analysis with R
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Develops fundamental theory behind linear regression, which is core to data analysis
Emphasizes the application of learned concepts through data examples
Utilizes the free and widely used statistical software R and RStudio
Covers a comprehensive range of topics, from basic to advanced concepts in linear regression
Provides a strong foundation for further study in statistics and data analysis
Taught by Mine Çetinkaya-Rundel, an experienced instructor in the field
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