Harvard University is currently offering a skill development free online course of Statistics and R Programming at edX. This is the first part of the specialization Data Analysis for Life Sciences. This course aims to guide all the participants to learn the programming in R and about Statistics.
The course covers the basic concepts of Statistics and R Programming for analyzing data in life sciences. Students have an opportunity to learn about what the statistical inference is and how to analyze the data using R.
Course At A Glance
- Length: 4 weeks
- Effort: 2-4 hours/week
- Subject: Biology & Life Sciences
- Institution: Harvard University
- Languages: English
- Level: Intermediate
- Price: Free, Add a Verified Certificate for $50
- Certificate Available: Yes
- Session: Self-Paced
Harvard University has teamed up with edX to bring this course Data Analysis for Life Sciences 1: Statistics and R for the participants. The Harvard University is one of the world’s most highly-respected universities which is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally.
EdX is a not-for-profit online education venture that provides you the latest MOOCs from best universities of the world and helps you create effective online teaching and learning experiences in a collaborative, private environment.
About This Course
This course will help you to master the basics of R programming as well as Statistics and provide R programming examples in a way that will help make the connection between concepts and implementation. This course also describes robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches.
The R language is widely used among statisticians and data miners for developing statistical software and data analysis. In short, R is a programming language and software environment for statistical computing and graphics.
Why Take This Course?
This is a free online course and by using R scripts to analyze data, you will learn the basics of conducting reproducible research.
Participants will receive an instructor-signed certificate with the institution’s logo to verify your achievement. The course is rich in high-quality text, images, video, audio and interactive elements to support your learning.
After the completion of this course participants will learn:
- How to read and write the data in R
- Basic Concepts of Statistics
- Control structures, functions, scoping rules, dates and times
- Simulation, code profiling
- Random variables
- Inference: p-values and confidence intervals
- Exploratory Data Analysis
- Non-parametric statistics
- Rafael Irizarry
Professor of Biostatistics T.H. Chan School of Public Health, Harvard University
- Michael Love
Postdoctoral Fellow T.H. Chan School of Public Health, Harvard University
Basic programming knowledge & basic knowledge of math