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.

Prerequisites:

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

Objectives

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.