Probability, Distribution Theory and Inference

This information is for the 2013/14 session.

Teacher responsible

Dr Konstantinos Kalogeropoulos COL.6.10 and Dr Erik Baurdoux COL.6.04


This course is compulsory on the BSc in Actuarial Science and BSc in Statistics with Finance. This course is available on the BSc in Accounting and Finance, BSc in Business Mathematics and Statistics, BSc in Econometrics and Mathematical Economics, BSc in Mathematics and Economics and BSc in Mathematics with Economics. 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 Elementary Statistical Theory (ST102) and Mathematical Methods (MA100).

Students who have not taken these courses should contact Dr Kalogeropoulos

Course content

The course covers the probability, distribution theory and statistical inference needed for third year courses in statistics and econometrics.

Michaelmas term (Dr Erik Baurdoux): Events and their probabilities. Random variables. Discrete and continuous distributions. Moments, moment generating functions and cumulant generating functions. Joint distributions and joint moments. Marginal and conditional densities. Independence, covariance and correlation. Sums of random variables and compounding. Multinomial and bivariate normal distributions. Law of large numbers and central limit theorem.

Lent term (Dr K Kalogeropoulos): Functions of random variables. Sampling distributions. Criteria of estimation: consistency, unbiasedness, efficiency, minimum variance. Sufficiency. Maximum likelihood estimation. Confidence intervals. Tests of simple hypotheses. Likelihood ratio tests. Wald tests, score tests.


20 hours of lectures, 9 hours of seminars and 10 hours of help sessions in the MT. 20 hours of lectures, 10 hours of seminars and 10 hours of help sessions in the LT. 4 hours of lectures in the ST.

Formative coursework

Students will be expected to produce 4 pieces of coursework in the MT and LT.

Indicative reading

G C Casella & R L Berger, Statistical Inference (primary reading); R Bartoszynski & M Niewiadomska-Bugaj, Probability and Statistical Inference (stresses comprehension of concepts rather than mathematics, complimentary reading only); J Jacod & P Protter, Probability Essentials (for further reading, a more advanced text on probability, using measure theoretic concepts and tools, still very accessible).


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

Key facts

Department: Statistics

Total students 2012/13: 121

Average class size 2012/13: 41

Value: One Unit

Guidelines for interpreting course guide information

PDAM skills

  • Problem solving
  • Application of information skills
  • Application of numeracy skills
  • Specialist skills