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.
Functions (part 1)
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Skills You'll Learn
Data Analysis, Debugging, R Programming, Rstudio
Reviews
4.5 (22,190 ratings)
- 5 stars68.07%
- 4 stars22.14%
- 3 stars5.82%
- 2 stars2.08%
- 1 star1.86%
EJ
Jul 11, 2016
Excellent course! I already knew a lot about R - but this class helped me solidify what I already knew, taught me lots of new tricks, and now I have a certificate that says I know `something' about R!
JM
Aug 11, 2019
Very challenging, but good course. I've been programming in R for over a year, but there were still some things for me to pick up in this class. Assignments were a challenge, but satisfying to tackle.
From the lesson
Week 2: Programming with R
Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.
Taught By
Roger D. Peng, PhD
Professor of Statistics and Data Sciences
Jeff Leek, PhD
Chief Data Officer, Vice President, and J Orin Edson Foundation Chair of Biostatistics in Public Health Sciences
Brian Caffo, PhD
Professor, Biostatistics