Computing for Data Analysis

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, discuss 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, creating informative data graphics, accessing R packages, creating R packages with documentation, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.

A student who has completed this course is able to:

• Read formatted data into R
• Subset, remove missing values from, and clean tabular data
• Write custom functions in R to implement new functionality and making use of control structures such as loops and conditionals
• Use the R code debugger to identify problems in R functions
• Make a scatterplot/boxplot/histogram/image plot and modify a plot with custom annotations
• Define a new data class in R and write methods for that class