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.
Simulation - Random Sampling
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Skills You'll Learn
Data Analysis, Debugging, R Programming, Rstudio
Reviews
4.5 (21,977 ratings)
- 5 stars68.13%
- 4 stars22.14%
- 3 stars5.82%
- 2 stars2.06%
- 1 star1.82%
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.
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 4: Simulation & Profiling
Taught By
Roger D. Peng, PhD
Associate Professor, Biostatistics
Jeff Leek, PhD
Associate Professor, Biostatistics
Brian Caffo, PhD
Professor, Biostatistics
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