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
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Probability — univariate and multivariate distributions, moments, generating functions
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Statistical inference — maximum likelihood, method of moments, Cramér-Rao lower bound
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Hypothesis testing — likelihood ratio test, Wald test, Neyman-Pearson lemma
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Confidence intervals — exact and approximate intervals, bootstrap methods
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Linear regression — OLS, model checking, F-tests, variable selection, multicollinearity
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Generalised Linear Models — Poisson, Gamma, inverse Gaussian, logistic regression
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Bayesian statistics — prior distributions, posterior, credibility theory, Bühlmann model
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Time series — stationarity, autocorrelation, ARIMA models, Box-Jenkins methodology
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Simulation — inverse transform method, acceptance-rejection, Monte Carlo applications
Career Outcomes
Typical Roles After Clearing
Actuarial Analyst, Pricing Analyst, Data Scientist (Insurance), Analytics Consultant
Expected Salary
₹5–9 LPA with CS1 cleared
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Ravi Sir's Exam Tip
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."
Neha Verma
Senior Actuarial Analyst, EY Actuarial Services
