Welcome to this comprehensive self-study material designed to cater to various learner profiles in at first understanding, then using and last mastering R statistical language. Each presentation is designed as a micro-learning session: feel free to ask any question in the issue tracking system.
As UNHCR staff, note that the content shared here is designed as an introduction and not as an official certification that could be registered in your personal professional profile. For certification, please refer to the corresponding workday training. Workday Training are referenced, when relevant, in the last resource slide of each presentation.
At the foundational 1st level, participants will gain a solid understanding of what R is and why to it. Without entering into “scripts”, you will understand what you can gain to use apps created with R or to nudge your team to work through R scripts, functions and packages.
An introduction to Analysis Reproducibility
Moving on to the 2nd level, learners should acquire skills in data manipulation and visualization within R scripts, empowering them to uncover insights from diverse datasets.
Data Manipulation and Visualization using
{refugees}&{unchrthemes}
Progressing to the 3rd level, participants will delve into the first stage of automation, learning the effective use of functions, enhancing their ability to streamline and automate data analysis tasks, leveraging the power of R Markdown for creating dynamic reports, facilitating clear and reproducible communication of analytical findings
From Scripts to Functions: An illustration with
{unhcrplot}, access data through API with{robotoolbox},{rhdx},{riddle},{popdata},{activityinfo-R}
“Work as a Team”: Collaboration through Version Control on Github.
Build data pipeline with Report Template with
{unhcrdown}to set up reproducible analysis pipeline
Analysis Automation Tips with Posit Connect: An example with weekly report
The 4th level focuses on creating R packages, fostering a deeper understanding of code organization and sharing solutions across the R community.
Package your knowledge: Development, Documentation & Testing with
{fusen}, illustrated with {unhcrdataportal}
Finally, at the advanced 5th level, participants will embark on the journey of creating compnion app to deliver the power of R to less technical users
Create Shiny Companion App with
{Graveler}
{A2SIT}Kobo Data Collection Management with {HighFrequencyChecks}
Kobo Survey Data Exploration with {KoboCruncher}
Apply Indicator calculations for RMS] with {IndicatorCalc}