Statistical Data Analysis with R Training Course

This five-day, hands-on course builds the skill to analyse data in R from the ground up, from importing and wrangling data to modelling and visualisation. It covers the R and RStudio environment, data wrangling, descriptive and inferential statistics, regression, and data visualisation. Participants leave able to analyse data in R, write clear scripts, and produce high quality charts, with no prior programming required.

R has become one of the most powerful and popular tools for data analysis anywhere, and it is free. It is used across research, official statistics, data science and evaluation, and its visualisation capabilities are second to none. Its one barrier is that it is code based, which can feel daunting to those who have never programmed. This course removes that barrier.

It builds R from the ground up. It covers the R and RStudio environment, data wrangling with the modern tidyverse approach, descriptive and inferential statistics, regression for modelling, and the production of high quality visualisations. No prior programming is assumed; the course teaches the code patiently, building from first commands to a complete analysis. Participants leave able to import and wrangle data in R, run and interpret the main analyses, produce excellent charts, and write clear, reusable scripts. The course is hands-on, with every participant writing and running R code throughout.

• Navigate the R and RStudio environment confidently and run code efficiently
• Understand core R objects, data structures and packages relevant to applied data analysis
• Import data from common file formats and prepare it for analysis in R
• Clean, transform, recode and manage variables using a structured workflow
• Use modern data-wrangling techniques to filter, group, summarise and reshape datasets
• Produce descriptive statistics and exploratory summaries that reveal the structure of the data
• Conduct and interpret common inferential techniques including t-tests, ANOVA, chi-square tests and correlation
• Build and interpret simple linear, multiple linear and introductory logistic regression models
• Produce clear and informative data visualisations using modern R tools
• Write clean, reusable and well-documented scripts that support reproducible analysis
• Communicate findings accurately in tables, charts and narrative summaries

This course is suitable for professionals who want to analyse and visualise quantitative data in R, including:

• Researchers, research assistants and academic staff
• Monitoring and evaluation officers and programme analysts
• Data analysts and aspiring data scientists
• Public health, epidemiology and social science professionals
• Government, NGO and development sector staff working with data
• Statistics officers and information management personnel
• Consultants and professionals seeking a free, scalable analytical tool
• Anyone moving from spreadsheet analysis to code-based statistical work

The course is delivered in a hands-on computer lab format. Each technique is demonstrated and then coded immediately by participants on real and realistic datasets, building scripts from first commands upward. The focus is on doing and understanding, and a daily practical session takes an analysis from data to findings.

•Live demonstration and guided coding in R and RStudio

•Hands-on analysis of real and realistic datasets

•Building scripts from first commands upward

•Step by step interpretation of output

•A daily practical session and a final analysis project

Organisations whose staff complete this course can expect:

• Stronger internal capability for data analysis and visualisation at no software licence cost
• More reproducible and transparent analytical workflows
• Better quality evidence for research, reporting, programme management and decision-making
• Improved ability to clean, analyse and interpret existing datasets in-house
• Reduced dependence on external analysts for routine statistical work
• Stronger data visualisation and communication of findings
• A scalable analytical capability that can support more advanced data work over time
• A more technically capable team able to work confidently in a modern code-based environment

Participants completing this course will gain:

• Confidence in using R as a practical analytical tool rather than an intimidating programming language
• The ability to build reusable scripts for data cleaning, analysis and visualisation
• Stronger data wrangling capability and a more disciplined approach to analysis
• Greater confidence in interpreting statistical results and explaining them clearly
• A valuable and transferable skill in one of the world’s most widely used analytical tools
• Improved ability to produce publication-quality charts and visual outputs
• A scalable analytical workflow that can grow into more advanced modelling, reporting and research work
• Greater independence in handling data-intensive tasks without relying on proprietary software

At Strategic Revenue Africa, our certification goes beyond proof of attendance—it represents practical competence and measurable capability. Upon successful completion of our training programs, participants are awarded a Certificate of Completion from Strategic Revenue Africa, recognizing their ability to apply acquired knowledge in real-world settings. As an organization focused on architecting sustainable revenue and strengthening organizational performance, our certifications signal that participants are equipped with skills that drive results, not just theory.

Basic computer literacy is required. No prior programming, R or advanced statistics experience is assumed. The course is designed for complete beginners as well as for participants who have some exposure to R but want a more structured and applied understanding of how to use it for real analysis. A basic familiarity with data, spreadsheets, survey results or research datasets will be helpful but is not essential. Participants should have access to R and RStudio during the course; both are free to install and use.