What you'll learn
Week 1: Background, Getting Started, and Nuts & Bolts
Week 2: Programming with R
Week 3: Loop Functions and Debugging
Week 4: Simulation & Profiling
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.
The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
Access to a computer or mobile device with an internet connection.
Motivation to learn!
There are no special materials or prerequisite knowledge required for this course.
Who this course is for
Students who are already familiar with this field
Students willing to put in a couple hours to learn about R Programming
Advanced students wanting to add another skill to their portfolio
Roger D. Peng, PhD – Associate Professor, Biostatistics – Bloomberg School of Public Health, Jeff Leek, PhD – Associate Professor, Biostatistics – Bloomberg School of Public Health, Brian Caffo, PhD – Professor, Biostatistics – Bloomberg School of Public Health
This course includes
Option for learning at your own pace
Videos and reading material about the course
Assessed tasks with feedback from other course participants
Evaluated tests with feedback
Evaluated programming tasks