ST227      Half Unit
Survival Models

This information is for the 2019/20 session.

Teacher responsible

Dr George Tzougas


This course is compulsory on the BSc in Actuarial Science. This course is available on the BSc in Business Mathematics and Statistics, BSc in Mathematics, Statistics, and Business and BSc in Statistics with Finance. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.


Students must have completed Mathematical Methods (MA100) and Elementary Statistical Theory (ST102).

Course content

An introduction to stochastic processes with emphasis on life history analysis and actuarial applications. Principles of modelling; model selection, calibration, and testing; Stochastic processes and their classification into different types by time space, state space, and distributional properties; construction of stochastic processes from finite-dimensional distributions, processes with independent increments, Poisson processes and renewal processes and their applications in general insurance and risk theory, Markov processes, Markov chains and their applications in life insurance and general insurance, extensions to more general intensity-driven processes, counting processes, semi-Markov processes, stationary distributions. Determining transition probabilities and other conditional probabilities and expected values; Integral expressions, Kolmogorov differential equations, numerical solutions, simulation techniques. Survival models - the random life length approach and the Markov chain approach; survival function, conditional survival function, mortality intensity, some commonly used mortality laws. Statistical inference for life history data; Maximum likelihood estimation for parametric models, non-parametric methods (Kaplan-Meier and Nelson-Aalen), regression models for intensities including the semi-parametric Cox model and partial likelihood estimation; Various forms of censoring; The technique of occurrence-exposure rates and analytic graduation; Impact of the censoring scheme on the distribution of the estimators; Confidence regions and hypothesis testing.


20 hours of lectures and 10 hours of seminars in the LT. 3 hours of lectures and 1 hour of seminars in the ST.

Students on this course will have a reading week in week 6 where they will be given review exercises to work on based on the first 5 weeks of the course.

Formative coursework

Compulsory written answers to two sets of problems.

Indicative reading

S Ross, Stochastic Processes; R Norberg, Risk and Stochastics in Life Insurance; The Institute of Actuaries, Core reading Subject CT4. For full details of the syllabus of CT4, see


Exam (100%, duration: 3 hours) in the summer exam period.

Key facts

Department: Statistics

Total students 2018/19: 109

Average class size 2018/19: 36

Capped 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Team working
  • Problem solving
  • Application of numeracy skills
  • Specialist skills