Introduction to Linear Models and Matrix Algebra
Perform matrix operations
Learn to use R programming to apply linear models to analyze data in life sciences.
2-4 hours a week
What You'll Learn
Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. In this introductory online course in data analysis, we will use matrix algebra to represent the linear models that commonly used to model differences between experimental units. We perform statistical inference on these differences. Throughout the course we will use the R programming language to perform matrix operations.
The course will be delivered via edX and connect learners around the world. By the end of the course, participants will understand the following concepts:
- Matrix algebra notation
- Matrix algebra operations
- Application of matrix algebra to data analysis
- Linear models
- Brief introduction to the QR decomposition
Your Instructors
Michael Love
Assistant Professor, Departments of Biostatistics and Genetics at UNC Gillings School of Global Public Health
Read full bio.
Ways to take this course
When you enroll in this course, you will have the option of pursuing a Verified Certificate or Auditing the Course.
A Verified Certificate costs $219 and provides unlimited access to full course materials, activities, tests, and forums. At the end of the course, learners who earn a passing grade can receive a certificate.
Alternatively, learners can Audit the course for free and have access to select course material, activities, tests, and forums. Please note that this track does not offer a certificate for learners who earn a passing grade.