Statistical Methods for Data Science 2 in R

Statistical Methods for Data Science 2 in R @ UTA. Dr. Bian. Spring 2025

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Lab

Labs section of the course.

Development Environment Setup

There are several methods to setup your initial R environment. You can run R in a GUI via RStudio, VS Code, a Jupyter notebook via a web browser, or on the command line in Bash. For beginner-friendly RStudio, VS Code, or Jupyter notebooks is recommended.

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Getting Started in Bash

To get a workflow and development environment started in bash see Github documentation to install this repository into your local machine: Cloning a Repository

Bash Development Workflow

Install R:

sudo apt install r-base

Run R Console Environment:

R

Alternatively you can run an R workflow environment directly in Bash with the following commands:

# Create an R script
nano hello.R

# Run R script
Rscript hello.R

Resources and Documentation

• Visual Studio Code: VS Code Interactive Development Environment
• RStudio: RStudio Interactive Development Environment
• Jupyter Notebooks: Jupyter Interactive Notebooks. To work with R in Jupyter Notebooks, install the R kernel provided in the links. See Jupyter Notebook's Github repository for more information - link
• R: About The R Project
• R kernel: The R kernel for workflows and development in Jupyter-based enviornments.
• The R programming language: Documentation

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