ICJIA R Workshop

This workshop is developed to offer a gentle introduction to the R programming language for ICJIA researchers who want to leverage the power and flexibility of R to improve their technical prowess as researcher.

Visit the official website for the workshop for more information, including the workshop schedule and course materials: https://bobaekang.github.io/icjia-r-workshop/

Workshop curriculum

The workshop consists of six separate modules which are meant to be followed in order. The goal of this workshop is help its participants to get familiar with basic concepts and tools for using R for data analysis tasks and research projects.

Module 1: Introduction to R

In this module, workshop participants will be introduced to the programmatic approach to research. Then they will learn what the R language is as well as the benefits of using R for their research projects. They will also be introduced to the R Studio IDE. An overview of the entire workshop curriculum is provided at the end of the module.

Module 2: R basics

Workshop participants will learn the basic building blocks of R language. Once participants gain some knowledge in the fundamental topics, they will be introduced to the popular tidyverse framework and provided with a recommendation as to a “good” style for coding in R.

• Part 1: Fundamentals of R programming
• Part 2: Gearing up for data analysis

Module 3: Data analysis with R

This module focuses on manimuplating and transforming tabular data using R. Workshop participants will learn how to import data into R environment and use the popular “tidyverse” syntax to clean and analyze data. Specifically, key functions in dplyr, tidyr, stringr, and lubridate packages will be covered.

• Part 1: Getting started with tidyverse
• Part 2: More on data analysis

Module 4: Data visualization with R

In this module, workshop participants will get started with generating plots to visually present and communicate insights from data. The main focus of this module is the popular ggplot2 package for data visualization. Participants will also be introduced to some options for generating maps and interactive plots.

• Part 1: The Grammar of Graphics
• Part 2: Maps and interactive plots

Module 5: Statistical modeling with R

In this module, workshop participants will learn how to conduct basic statistical analysis with R, including Student’s t-test, analysis of variance (ANOVA), basic linear regression model, and generalized linear models. Participants will also be provided with resources for more advanced statistical modeling.

• Part 1: Basics of statistical modeling
• Part 2: Options for advanced modeling

Module 6: "To Infinity and Beyond"

This module will invite workshop participants to explore the power of R programming beyond basic data analysis, visualization, and statistical modeling. Topics explored here include sharing the results of research and analysis in the form of documents, slideshows, interactive application/dashboards, and more. Participants will also practice leveraging the power of the Internet to facilitate their search for answers to specific questions.

• Part 1: Sharing your work
• Part 2: Leveraging online resources

Some great online resources

Here is a running list of great (free) onlnie resources on learning R:

• "An Introduction to R" by CRAN
• R for Data Science by Grolemund, G. & Wickham, H.
• Cheatsheets by RStudio
• R-bloggers
• Quick-R by Kabacoff, R. I.
• R Tutorial by Yau, C.
• R Tutorial by Black, K.
• UC Business Analytics R Programming Guide by University of Cincinnati
• "R Tutorials" by DataMentor
• And... Google!