CS1 – Actuarial Statistics (Theory + R Programming)

Master the core statistical techniques and R programming tools essential for modern actuaries.

Course Overview

CS1 is the statistics paper for actuarial students, combining mathematical statistics (Part A) and statistical computing using R programming (Part B). This course lays the foundation for applying statistical reasoning to real-life problems in insurance, finance, and data-driven decision-making.

CS1 is offered by both IAI (India) and IFoA (UK) and is divided into:

•  CS1A – Statistical theory & probability
•  CS1B – Application using R programming

 What You Will Learn

 CS1A – Statistical Theory

• Probability theory and distributions
• Statistical inference (estimation, confidence intervals)
• Hypothesis testing (t-tests, chi-square, etc.)
• Correlation and regression models
• Time series and smoothing techniques
• Bayesian statistics and credibility theory
• Applications in insurance and risk modelling

 CS1B – R Programming & Application

• Introduction to R programming basics
• Writing functions, data handling & manipulation
• Plotting and visualisation in R
• Simulating distributions and calculating probabilities
• Regression and statistical modelling using R
• Automating statistical analysis
• Model building & testing using real-life actuarial data

 Why Choose CS1?

• Builds statistical thinking essential for actuarial modelling
• Introduces data analysis using R, a key tool in industry
• Sets the stage for subjects like CS2, SP1, SP5 and data science roles
• Strong placement value when combined with CM1

 Real-World Applications

• Claim modelling and fraud detection
• Health insurance data analysis
• Customer retention and churn prediction
• Investment return modelling
• Mortality and morbidity data evaluation
• Regression & trend forecasting for business metrics

 Exam Structure

 Passing Criteria

 Tips from S MONK to Crack CS1

• Master formulas + interpretation in CS1A
• Practice R code writing from Day 1 – avoid rote learning
• Build projects like: mortality forecasting, claim simulation, etc.
• Revise PYPs + attempt S MONK’s mock exam series
• Learn to debug R code independently

 Course Fee Breakdown

 Who Can Join?

 12th pass or graduates from any stream

 Basic math/stats background helpful (not mandatory)

 Ideal for students aiming to enter data, insurance, or actuarial fields