The R Language - The Good, The Bad & The Ugly

Explore the strengths and weaknesses of the R programming language for data analysis in this 38-minute conference talk from GOTO Aarhus 2012. Delve into why data analysis requires its own domain-specific language and how developers can leverage R's capabilities while mitigating its limitations. Learn about R's unique features, including vectorization and statistical notation, as well as its challenges such as syntax issues and performance concerns. Examine practical examples of linear regression and data set analysis to understand R's application in real-world scenarios. Gain insights into R's position in the data science ecosystem, comparing it with other languages like Python. Discover valuable resources for further learning and development in R programming.

Intro
What is R
R is not a language
Excel has a language
Emacs has a programming language
Data Analysis Competition
Bioinformatics
Using R
Smoking
prickly syntax
statisticians
what is statistics
the domain
statistics
Python vs R
Linear regression example
Notation
Regression
Data Set Example
Data Set Analysis
Language Features
Vectorization
Slow
Tool Support
Intention
Problem
Our Inferno
The Good Parts
Resources