COURSE CODE: CCPOP-GHANA 2026 SC004

PRACTICAL DATA ANALYTICS WITH R & RSTUDIO FOR DECISION-MAKING

 

Background

Data is the “new oil” and in modern data-driven economy, researchers, professionals and policy and decision makers are expected to collect, analyze, interpret and effectively communicate insights from data. Nonetheless, wrestling with conventional tools like spreadsheets often constrains the capacity to work with large datasets, automate workflows, and ensure reproducibility.

R and RStudio provide an open-source, powerful environment for statistical computing, data wrangling, visualisation and reporting. R is extensively used in academia, industry and policy settings, enabling practitioners to move from descriptive analysis to predictive insight.

This one-day hands-on workshop introduces participants to the fundamental building blocks of statistical programming in R with a practical emphasis, including data structuring, cleaning, transformation, regression analysis, and reporting using RMarkdown.

Goals

This one-day training aims to equip participants with foundational and practical skills in R and RStudio for data analysis and decision-making.

Participants will learn core workflows including data cleaning, transformation, visualization, and statistical analysis using tidyverse tools, and will build reproducible reports using RMarkdown.

The session concludes with a practical exercise using real datasets and R-based analysis.

Learning Outcomes

  • Understand and navigate R and RStudio environment

  • Work with vectors, matrices, data frames, and tibbles

  • Apply variables, operators, and functions effectively

  • Import, clean, and transform data using tidyverse

  • Perform exploratory data analysis (EDA)

  • Compute correlation and regression models

  • Create visualizations using ggplot2

  • Develop reproducible reports using RMarkdown

  • Manage workflows using scripts and projects

Requirements

  • Participants can come from any discipline or sector

  • No prior programming knowledge required

  • Interest in data analysis and statistics is recommended

  • Basic familiarity with spreadsheets is an advantage

  • Must be a registered conference participant

Hardware Requirements

  • Bring Your Own Laptop

  • R and RStudio must be installed (installation guide provided)

Recommended Reading

  • Wickham, Çetinkaya-Rundel & Grolemund – R for Data Science (2nd Edition)

  • Grolemund – Hands-On Programming with R

  • Kabacoff – R in Action

  • Xie, Allaire & Grolemund – R Markdown: The Definitive Guide