# Rich Lab:Free Courses

### From OpenWetWare

- Back to SWES-MEL

**Computing for Data Analysis**[1]

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.

**Statistical Reasoning**[2]

Statistical Reasoning introduces students to the basic concepts and logic of statistical reasoning and gives the students introductory-level practical ability to choose, generate, and properly interpret appropriate descriptive and inferential methods. Provides a great introduction to different statistical softwares including Microsoft Excel, Minitab, the open source R software, TI calculator, and StatCrunch.

**Code School: Try R**[3]

R is a tool for statistics and data modeling. The R programming language is elegant, versatile, and has a highly expressive syntax designed around working with data. R is more than that, though — it also includes extremely powerful graphics capabilities. If you want to easily manipulate your data and present it in compelling ways, R is the tool for you.