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HarvardX: Introduction to Linear Models and Matrix Algebra

Learn to use R programming to apply linear models to analyze data in life sciences.

4 weeks
2–4 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

116,590 already enrolled! After a course session ends, it will be archivedOpens in a new tab.
Starts Mar 19
Ends Nov 27

About this course

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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.

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. You will need to know some basic stats for this course. 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.

These courses make up two Professional Certificates and are self-paced:

Data Analysis for Life Sciences:

Genomics Data Analysis:

This class was supported in part by NIH grant R25GM114818.

At a glance

  • Language: English
  • Video Transcripts: اَلْعَرَبِيَّةُ, Deutsch, English, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
  • Associated skills:Statistical Inference, Statistics, Algebra, R (Programming Language), Bioconductor (Bioinformatics Software), Life Sciences, Functional Genomics, Biology, Experimental Design, Data Warehousing, Data Analysis, Matrix Algebra, Software Engineering, Linear Model

What you'll learn

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

More about this course

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HarvardX Honor Code

HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

HarvardX Nondiscrimination/Anti-Harassment Statement
Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form.

HarvardX Research Statement
HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more.

This course is part of Data Analysis for Life Sciences Professional Certificate Program

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Expert instruction
4 skill-building courses
Self-paced
Progress at your own speed
4 months
2 - 4 hours per week

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