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.
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Connections: Interfaces to the Outside World
Skills You'll Learn
Critical Thinking, Data Analysis, Computer Programming, Rstudio, General Statistics, Programming Principles, Debugging, Problem Solving, Data Structures, Computer Programming Tools, Statistical Programming, R Programming
Reviews
4.5 (22,310 ratings)
- 5 stars68.05%
- 4 stars22.14%
- 3 stars5.82%
- 2 stars2.08%
- 1 star1.89%
RD
Mar 2, 2016
A great introduction to slightly more complicated R programming. Basic concepts covered well and it builds nicely to the point where you feel like you can apply your knowledge to real world examples
DK
Feb 2, 2016
The content is superbly designer for a beginner. The Swirl assignments need to make compulsory. Infact they contributed more to the learning process. More Swirl contents will make the course richer.
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