The R Programming Module, coordinated by Dr Asha Kamath (Associate Director, PSPH; HoD, Department of Applied Statistics and Data Science, PSPH) and supported by PSPH PhD students - Mr Nagarjuna, Mr Nehal, and Ms Varsha, was held from July 07, 2025, for 10 days, aiming to develop foundational to advanced skills in R programming with hands-on applications in data handling, statistical analysis, and predictive modelling. The training began with sessions on R installation, data management, and core programming concepts such as data types, structures (vectors, matrices, lists, arrays), loops, functions, and object-oriented programming. Days 3 to 5 focused on Exploratory Data Analysis (EDA), including statistical foundations, visualisation of categorical and quantitative data, and computation of descriptive statistics, culminating in a practical assignment with presentations. Days 6 and 7 covered statistical inference techniques like parametric and non-parametric tests, correlation, and cross-tabulations, followed by another practical assignment. The final phase (Days 8–10) introduced predictive modelling techniques including linear and logistic regression, unsupervised learning (hierarchical and k-means clustering), and supervised learning (kNN, Na?ve Bayes), and concluded with a comprehensive report writing and presentations integrating all concepts learned.

This two-credit course offered by the Department of Applied Statistics and Data Science (DASDS), Prasanna School of Public Health (PSPH), 沙巴体育 Academy of Higher Education (MAHE) offered an exciting opportunity for a novice to begin programming in R and learning how to use R for effective data analysis. This module focused on step-by-step learning for building competency to develop analytical skills to carry out predictive modelling on big data.