CS2B – Statistical Modelling with R

Course Overview

CS2B trains students to apply risk and survival modelling techniques using R—the statistical language of choice for actuaries worldwide. Through structured datasets and practical assignments, students will implement, simulate, and interpret real-life actuarial models, from claim modeling to mortality forecasting.

Skills Developed

• Use of R to simulate and visualize loss distributions and reinsurance structures

• Building and evaluating time series models (ARIMA, random walks, cointegration)

• Programming Markov chains and survival models with age/duration-dependent intensities

• Kaplan-Meier, Nelson-Aalen, and Cox proportional hazards model implementation

• Estimating transition intensities from censored and uncensored datasets

• Applying machine learning algorithms (PCA, clustering, classification) in actuarial contexts

Outcome

CS2B enables students to bridge actuarial theory with technical execution. On completing this course, students will be capable of transforming actuarial problems into coded models and statistical outputs—skills increasingly critical in data-driven actuarial roles across life, health, and general insurance.