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.
Control Structures - While loops
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Skills You'll Learn
Data Analysis, Debugging, R Programming, Rstudio
Reviews
4.5 (21,963 ratings)
- 5 stars68.12%
- 4 stars22.14%
- 3 stars5.83%
- 2 stars2.06%
- 1 star1.83%
MR
May 11, 2020
Really interesting course. The interactive coding sessions with swirl are especially useful. Would be great, if you provided sample solutions for the programming assignments, in particular for week 4.
WH
Feb 2, 2016
"R Programming" forces you to dive in deep.
These skills serve as a strong basis for the rest of the data science specialization.
Material is in depth, but presented clearly. Highly recommended!
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
Associate Professor, Biostatistics
Jeff Leek, PhD
Associate Professor, Biostatistics
Brian Caffo, PhD
Professor, Biostatistics
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