Statistics and R

R programming language in the context of statistical data and statistical analysis

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

Featuring faculty from:
Self-Paced
Length
4 weeks
2-4 hours a week
Certificate Price
$219
Program Dates
Start Statistics and R Today

What You'll Learn

This course teaches the R programming language in the context of statistical data and statistical analysis in the life sciences.

We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R code. We provide R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses. We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research.

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:

  • Random variables
  • Distributions
  • Inference: p-values and confidence intervals
  • Exploratory Data Analysis
  • Non-parametric statistics

Your Instructors

Image
Rafael Irizarry

Rafael Irizarry

Professor of Biostatistics at Harvard University
Read full bio.

Image
Michael Love

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.

Read More

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.

Read More

High-Dimensional Data Analysis

If you’re interested in data analysis and interpretation, then this is the data science course for you.

A focus on several techniques that are widely used in the analysis of high-dimensional data.

Read More

Introduction to Bioconductor

Learn what we measure and why in relevant biology.

Join Harvard faculty in this online course to learn the structure, annotation, normalization, and interpretation of genome scale assays.