Statistical Data Analysis using R Programming

About the course

This course provides an introduction to R programming and quantitative data analysis (exploring, summarizing, statistical analyzing, visualizing). Participants with interest in Programming languages that allow work to be explicit & documented, promoting experimentation and exploration, and recording work-­‐flow from start to finish will find this course useful and applicable.


This course is designed with beginners in mind and assumes no prior knowledge of statistics or quantitative research background. Participants are expected to come with their own laptops.

Course Outline:

  • Introduction to statistics, Univariate Analysis and Multivariate Analysis
  • Introduction to programming (R installation, basic syntax, Scripts – Documenting, commenting & sharing code).
  • Creating and Manipulating objects in R Objects in R – Vectors, Matrices, Dates & Times.
  • For Loops & Vectorization, Missing Values
  • Objects in R – Arrays, Data Frames and Lists Folder and File structure, Importing Data
  • Validating & Exploring Data, Manipulating Data -­‐ Summarizing, Sorting, Sub-­‐setting, Merging
  • Visualizing – Basic plotting, Histograms, Multi-­‐panel plotting, Boxplots, ggplot2
  • Creating functions and Installing Packages


The course will;

  • Introduce participants to R as a data analysis tool.
  • Introduce basic statistics for exploratory data analysis including methods for describing and summarizing variable distributions;
  • Provide essential skills in data manipulation including selecting sub-sets and recoding;
  • Introduce the visual representation of variables in scatter graphs, bar charts, and histograms.