- Syllabus
- Why learn R?
- Essential programs/packages
- Free resources
- R as a calculator
Jan 12, 2026
Today
Course Info
| Hyatt Green | Elie Gurarie | |
|---|---|---|
| Email: hgreen@esf.edu | Email: egurarie@esf.edu | |
| Phone: 315-470-4814 | Phone: 315-470-3817 | |
| Office: 201 Illick Hall | Office: 206 Illick Hall | |
| Office hours: W 1-2pm | Office hours: M 2-3pm |
Credits: 2
Meets: MW, 10:35-11:30am | 309 Baker
Course Materials Website: https://eligurarie.github.io/EFB654
Go to DRAFT Syllabus
Big changes coming this week.
This is hard! Why do this?
- Save your time
- building off of previously designed methods (by you or others)
- Improves the appearance of your work (R + other tools)
- Actually helps you perform better research
- take ‘bad’ shortcuts less often
- permits thorough criticism
- Organizes your work (which helps you do all of the above)
- Improves access to your work (e.g., research compendia)
- More research opportunities
- permits the analysis of ‘large’ data (and ‘big’ data)
- Big picture: Limits reproducibility/replicability `crisis’
- Future requirement of scientific journals
Ideal Habits During and After Class
- With R, you often plan and build a foundation to your analyses
- Not only learn R but also practice R
- Choose to use R even though it might cost you a little time in the beginning
- Encourage others to learn R
R and Associated Programs
| Tool | Type | Purpose |
|---|---|---|
| R | Programming Language | Statistical computing and graphics language for data analysis |
| RStudio | IDE (Integrated Development Environment) | User-friendly interface that makes working with R easier - provides code editor, console, and visualization tools all in one place |
| knitr | R Package | Evaluates and translates R code embedded in documents, enabling dynamic report generation |
| RMarkdown | R Package | Combines plain text with embedded R code, creating reproducible documents |
RStudio provides the workspace → RMarkdown documents contain your text and code → knitr processes the R code → Final document is produced (PDF, HTML, etc.)
What is R?
- Programming language
- it has its own syntax
- if you learn it, you can make R do stuff for you
- Programming environment
- Not just a list of tools
- but a “fully planned and coherent system”
- permits creation of new tools and new clusters of tools called packages
What does R do?
- statistics
- plotting
- data handling, manipulation, and efficient storage
- drafting
- designing websites
- developing interactive tools
- you can make R do pretty much anything (see r.bloggers)
Advantages of R
- Free, open source
- Seemingly endless number of packages for pretty much any type of data analysis you can imagine
- the latest analysis tools
- Large, usually helpful, community of users (see stackoverflow)
- Tools for communicating results (easily accessible through RStudio)
- LLM AI assistants like Claude, Gemini, ChatGPT know R well
Disadvantages of R
- Much of the written code you’ll see is sloppy
- Authors are focused on the results. Hasty.
- Diverse backgrounds
- Inconsistent
- Many packages for the same purpose
- Many special cases to remember
- Not that fast. Poorly written code can be really slow.
Redundant R Packages
from Lortie et al. 2020
Accessing R
- R
- R Studio
- Terminal (Mac)
R as a Calculator
- arithmetic
- basic functions
mean(),sd(),Sys.time() - help with specific functions
demo()to check out R capabilities
Accessing More R Resources
- CRAN
- Task Views
- Quick-R
- R-bloggers
- Advanced R
- stackoverflow
- Google (helps to know specific terms)
R Studio
- Itegrated Development Environment
- Offers quick point-and-click access to stuff you otherwise have to type in longhand
- files
- plots
- packages
- creating documents
- etc
- Requires R still
Go to R Studio
RMarkdown
- Drafting language designed to be simple and intuitive
- Allows embedding of R code
knitr
- ‘knits’ R code and output (plots, etc) into Rmarkdown
- Produces many different types of output
- html
- docx
- Does not do any analysis for you, just formats the output