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.
Data Types - Missing Values
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Skills You'll Learn
Data Analysis, Debugging, R Programming, Rstudio
Reviews
4.5 (22,251 ratings)
- 5 stars68.06%
- 4 stars22.13%
- 3 stars5.82%
- 2 stars2.08%
- 1 star1.88%
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!
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.
From the lesson
Week 1: Background, Getting Started, and Nuts & Bolts
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