Introduction to Linear Models and Matrix Algebra

The basics of linear models you need to know for data analysis in the life sciences.

About The Course

We will teach a review of linear algebra, including matrix notation and the concept of projections, which underlies many of the current tools for analyzing large-dimensional data. We will then use linear models to represent differences between experimental units and perform statistical inference on these differences.


  • Linear algebra: matrix notation, projections
  • Linear models

This class was supported in part by NIH grant R25GM114818.

This course is part of a larger set of 8 total courses:

PH525.1x: Statistics and R for the Life Sciences

PH525.2x: Introduction to Linear Models and Matrix Algebra

PH525.3x: Advanced Statistics for the Life Sciences

PH525.4x: Introduction to Bioconductor

PH525.5x: Case study: RNA-seq data analysis

PH525.6x: Case study: Variant Discovery and Genotyping

PH525.7x: Case study: ChIP-seq data analysis

PH525.8x: Case study: DNA methylation data analysis

Recommended Background

Basic programming, basic math, intro to statistics.