This course is for analysts who need to make decisions based on data. This course is for users that have a little experience with R: The Statistical Programming Language. R is a powerful open source programming language that is widely used for analyses of all kinds. R also has extensive graphical capabilities.

The course combines two elements: data visualisation (graphics), and statistical hypothesis testing (decision-making).

The data visualisation part is designed to cover a range of graphical methods, including:

  • Histograms
  • Density plots
  • QQ plots
  • Bar charts
    • Single series charts
    • Multiple series charts (stacked and unstacked)
  • Box-whisker plots
  • Scatter plots
    • Lines of best-fit
    • Multivariate scatter plots
  • Exporting graphics

The hypothesis testing part is designed to cover the basic analytical decision-making tools that underpin statistical analysis. Topics include:

  • Testing data distribution (normal distribution)
  • Differences tests:
    • t-test for normally distributed data
    • U-test for nonparametric data
  • Correlation
  • Association tests:
    • Chi-Squared test for association
    • Goodness of Fit tests
  • Analysis of Variance (ANOVA) for testing of multiple samples
  • Regression modelling

Who needs this course?

This course is for people who need to handle data and make decisions based on those data. Some knowledge of R would be helpful but no special knowledge of statistics is needed.

If you have any queries please email: or telephone: 029 2087 5260