### Course Information for Spring 2022

Lab Sessions |

Tues 8:30-9:20pm (Davis 308) |

Wed 7:30-8:20pm (Davis 308) |

Fri 12-12:50pm (Davis 102) |

### Instructor Information

Prof. Stephanie Taylor

Office: Davis 112

Typical Office hours in person: M 4-5pm, T 1-2pm, W 8:30-10pm, R 12-2pm

I often need to change my office hours to accommodate meetings. I post an image of my calendar at the beginning of each week on my home page.

### Course Description

An introduction to the programming language R and how it can be used for statistical analysis and visualization of data. Students will learn how to write basic R programs that can read, write, and manipulate data. They will make use of R functions for executing common statistical analysis and learn how to display the results using graphs and charts. Through a series of projects, students will get experience with writing their own functions, learn how to make use of R documentation and how to extend their own knowledge of the language.

### Learning Goals

- Students can read a simple R program and correctly predict its behavior.
- Students can write programs in R to read, write, and manipulate data.
- Students can write programs in R to execute common statistical analyses and generate visualizations of the results.
- Students have experience with the concepts of functions, modularity, and abstraction.
- Students have experience with R documentation and how to extend their knowledge on their own.

### Links to R Software

- You can install the software on your own computer (this is prefered if you want to keep your code and set-up working beyond your time at Colby)
- Install the R package.
- Install the RStudio Desktop

- You can use https://rstudio.colby.edu if you don't want to install software now.

### Links Resources for Learning R

- Quick-R Tutorial
- Advanced R (online book)
- Introduction to R by DataCamp
- The Comprehensive R Archive Network [CRAN]