EdX

Introduction to Linear Models and Matrix Algebra (edX)

Offered by HarvardX, Harvard University,

Learn to use R programming to apply linear models to analyze data in life sciences. Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. In this introductory data analysis course, 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.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

This course is part of the Data Analysis for Life Sciences XSeries.

These courses make up 2 XSeries and are self-paced:
Data Analysis for Life Sciences:
PH525.1x: Statistics and R for the Life Sciences
PH525.2x: Introduction to Linear Models and Matrix Algebra
PH525.3x: Statistical Inference and Modeling for High-throughput Experiments
PH525.4x: High-Dimensional Data Analysis
Genomics Data Analysis:
PH525.5x: Introduction to Bioconductor: annotation and analysis of genomes and genomic assays
PH525.6x: High-performance computing for reproducible genomics
PH525.7x: Case studies in functional genomics

What you'll learn:

Matrix algebra notation
Matrix algebra operations
Application of matrix algebra to data analysis
Linear models
Brief introduction to the QR decomposition

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Excel for Everyone: Core Foundations (edX)

EdX

The University of British Columbia,UBCx

Excel for Everyone: Core Foundations (edX)

Statistics & Data Analysis

Learn Excel fundamentals including data wrangling, spreadsheet management, and basic data analysis. This introductory Excel course will equip you with a strong foundational knowledge of Excel to organize, analyze and work with data. You will develop essential Excel skills, such as simple data wrangling and managing spreadsheets, along with a foundational understanding of business data analysis.

Self Paced

Self-Paced

Spreadsheets Excel Data Analysis

EdX

HarvardX,Harvard University

Data Science: R Basics (edX)

Statistics & Data Analysis Data Science

Build a foundation in R and learn how to wrangle, analyze, and visualize data. This course will introduce you to the basics of R programming. You can better retain R when you learn it to solve a specific problem, so you’ll use a real-world dataset about crime in the United States. You will learn the R skills needed to answer essential questions about differences in crime across the different states.

Self Paced

Self-Paced

Probability Machine Learning Inference

EdX

Babson College

Analytics for Decision Making (edX)

Management & Leadership Statistics & Data Analysis

Discover the foundational concepts that support modern data science and learn to analyze various data types and quality to make smart business decisions. Want to know how to avoid bad decisions with data? Making good decisions with data can give you a distinct competitive advantage in business. This statistics and data analysis course will help you understand the fundamental concepts of sound statistical thinking that can be applied in surprisingly wide contexts, sometimes even before there is any data! Key concepts like understanding variation, perceiving relative risk of alternative decisions, and pinpointing sources of variation will be highlighted.

Self Paced

Self-Paced

Data Analysis Decision Making Analytics

Data Processing and Analysis with Excel (edX)

EdX

Rochester Institute of Technology,RITx

Data Processing and Analysis with Excel (edX)

Statistics & Data Analysis

Learn to use Excel to organize and clean data so it can be manipulated and analyzed. In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

Self Paced

Self-Paced

Excel Data Analysis Microsoft Excel

EdX

Georgia Institute of Technology,GTx

Linear Algebra II: Matrix Algebra (edX)

Sci: Mathematics

This course takes you through roughly three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. Your ability to apply the concepts that we introduced in our previous course is enhanced when you can perform algebraic operations with matrices. At the start of this class, you will see how we can apply the Invertible Matrix Theorem to describe how a square matrix might be used to solve linear equations.

Self Paced

Self-Paced

Math Algebra Equations

EdX

École Polytechnique Fédérale de Lausanne,EPFLx

Algèbre Linéaire (Partie 1) (edX)

Sci: Mathematics

Un MOOC francophone d'algèbre linéaire accessible à tous, enseigné de manière rigoureuse et ne nécessitant aucun prérequis. Vous voulez apprendre l'algèbre linéaire, un précieux outil complémentaire à vos connaissances acquises durant vos études en économie, ingénierie, physique, ou statistique? Ou simplement pour la beauté de la matière? Alors ce cours est fait pour vous!

Self Paced

Self-Paced

Linear Algebra

EdX

École Polytechnique Fédérale de Lausanne,EPFLx

Algèbre Linéaire (Partie 2) (edX)

Engineering Sci: Mathematics

Self Paced

Self-Paced

Math Linear Algebra Algèbre Linéaire

EdX

University of Adelaide,AdelaideX

Programming for Data Science (edX)

CS: Programming Data Science

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced

Self-Paced

Programming Big Data Data Analysis

EdX

IBM

R Data Science Capstone Project (edX)

Statistics & Data Analysis

Apply various data analysis and visualization skills and techniques you have learned by taking on the role of a data scientist working with real-world data sets. In this capstone course, you will apply various data science skills and techniques that you have learned as part of the previous courses in the IBM Data Science with R or IBM Data Analytics with Excel and R Professional Certificate Programs.

Self Paced

Self-Paced

Statistics Data Analysis Linear Regression

Advanced Linear Algebra: Foundations to Frontiers (edX)

EdX

University of Texas at Austin,UTAustinX

Advanced Linear Algebra: Foundations to Frontiers (edX)

Sci: Mathematics Computer Science

Learn advanced linear algebra for computing. Linear algebra is one of the fundamental tools for computational and data scientists. In Advanced Linear Algebra: Foundations to Frontiers (ALAFF), you will build your knowledge, understanding, and skills in linear algebra, practical algorithms for matrix computations, and the analysis of the effects of floating-point arithmetic as performed by computers.

Self Paced

Self-Paced

Math Computing Algorithms

Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX)

EdX

Seoul National University,SNUx

Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX)

Economics & Finance Statistics & Data Analysis

This course teaches basic statistical concepts and explores many compelling applications of statistical methods using real-life applications of Statistics. Why do we study statistics? The field of statistics provides professionals and scientists withconceptual foundations and useful techniques for evaluating ideas, testing theories, and - ultimately -uncovering the truth in any situation.

Self Paced

Self-Paced

Statistics Regression Data Analysis

Inteligencia empresarial con Tableau (edX)

EdX

University of Naples Federico II,FedericaX

Inteligencia empresarial con Tableau (edX)

Statistics & Data Analysis

Aprovecha al máximo las funciones de Tableau, analiza los datos. Este curso se dirige a usuarios de Tableau que han madurado un sólido conocimiento del software en los cursos de nivel básico e intermedio.

Self Paced

Self-Paced

Data Analysis Business Intelligence Data Visualization