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Introduction to Linear Models and Matrix Algebra 
offered by Harvard University

Introduction to Linear Models and Matrix Algebra
 at 
Harvard University 
Overview

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

Duration

4 weeks

Mode of learning

Online

Difficulty level

Intermediate

Official Website

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Course Level

UG Certificate

Introduction to Linear Models and Matrix Algebra
 at 
Harvard University 
Highlights

  • Earn a certificate of completion
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Introduction to Linear Models and Matrix Algebra
 at 
Harvard University 
Course details

What are the course deliverables?
  • 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
  • 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.

Introduction to Linear Models and Matrix Algebra
 at 
Harvard University 
Curriculum

Data Science, Data Analysis, R, Statistics, Biology

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Introduction to Linear Models and Matrix Algebra
 at 
Harvard University 
Faculty details

Rafael Irizarry
Designation : Professor of Biostatistics, T.H. Chan School of Public Health
Michael Love
Designation : Assistant Professor, Departments of Biostatistics and Genetics, UNC Gillings School of Global Public Health

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Introduction to Linear Models and Matrix Algebra
 at 
Harvard University 
Contact Information

Address

1350 Massachusetts Ave, Cambridge, Massachusetts 02138, USA
Cambridge ( Massachusetts)

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