R, Quarto &
RStudio

Dr. Ajay Kumar Koli, PhD | SARA Institute of Data Science, India

Reproducible Research

“Research is reproducible when others can reproduce the results of a scientific study given only the original data, code, and documentation.”

Source: (Alston and Rick 2021)

Reproducible Research Requires:

1. Data - access to original data.

2. Code - others can read, learn & replicate results.

3. Documentation - complete information about how to conduct the study.

Data Science Project

Image source: Wickham, Cetinkaya-Rundel, and Grolemund (2023)

R Programming Language

“R is a free software environment for statistical computing and graphics.”

Download R from this link: https://www.r-project.org/

Practice R Software

1. Addition

2. Subtraction

3. Sequence

4. Combine

5. Function structure

6. Create an object

RStudio IDE

“The RStudio integrated development environment (IDE) is a set of tools built to help you be more productive with R and Python.”

Download R from this link: https://posit.co/download/rstudio-desktop/

Practice RStudio

1. An overview of RStudio IDE.

2. Create project in RStudio.

Quarto Publishing System

“An open-source scientific and technical publishing system to prepare articles & reports; presentations; dashboards; websites; books; and interactive documents.

To know more about Quarto: https://quarto.org/

Practice Quarto using RStudio

1. Create a Quarto document with HTML format.

2. Explain YAML, Text and Code Chunk

   • To know about the all Quarto YAML options.
   • To know about the Quarto text formating

R Packages

“a collection of functions, data and documentation that extends the capabilties of base R.” (Wickham, Cetinkaya-Rundel, and Grolemund 2023)

Image source: On 29 Nov 2024 Metacran | CRAN.

Practice Quarto

1. Explain Code Chunk
   • To know about the Quarto code chunk options
2. Install tidyverse package.

🤯 Your Turn

15:00

References

Alston, Jesse M., and Jessica A. Rick. 2021. “A Beginner’s Guide to Conducting Reproducible Research.” The Bulletin of the Ecological Society of America 102 (2): e01801. https://doi.org/10.1002/bes2.1801.

Wickham, Hadley, Mine Cetinkaya-Rundel, and Garrett Grolemund. 2023. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. 2nd ed. edition. Beijing Boston Farnham Sebastopol Tokyo: O’Reilly Media.