CS1 Actuarial Statistics
Probability, regression, and GLMs: the statistical toolkit every modern actuary uses daily.
About CS1
CS1 covers the statistical theory underlying all actuarial modelling: probability distributions, maximum likelihood estimation, regression, GLMs, Bayesian methods, and time series. As actuarial work becomes data-driven, CS1 has grown in strategic importance. Students who clear CS1 are immediately valuable to employers building pricing models and analytics tools.
Who is this for?
Students with A-level Maths or equivalent. Often taken alongside CM1. Students interested in data science, InsurTech, or analytics roles should prioritise CS1 early.
Complete Syllabus
- Probability: univariate and multivariate distributions, moments, generating functions
- Statistical inference: maximum likelihood, method of moments, Cramér-Rao lower bound
- Hypothesis testing: likelihood ratio test, Wald test, Neyman-Pearson lemma
- Confidence intervals: exact and approximate intervals, bootstrap methods
- Linear regression: OLS, model checking, F-tests, variable selection, multicollinearity
- Generalised Linear Models: Poisson, Gamma, inverse Gaussian, logistic regression
- Bayesian statistics: prior distributions, posterior, credibility theory, Bühlmann model
- Time series: stationarity, autocorrelation, ARIMA models, Box-Jenkins methodology
- Simulation: inverse transform method, acceptance-rejection, Monte Carlo applications
Career Outcomes
Actuarial Analyst, Pricing Analyst, Data Scientist (Insurance), Analytics Consultant
₹5–9 LPA with CS1 cleared
GLMs are the most tested area in recent years. Understand the exponential family, the link function, and the deviance, not just the mechanics.
“CS1 opened doors I did not expect. My employer at EY uses GLMs every day, and I was the only analyst in my batch who understood what was happening. That came entirely from S.MONK.”