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The Minor in Statistics is an undergraduate minor degree which is exclusively designed for Single Honors Mathematics students.
In order to complete this minor, students must take 20 ECTS credits of compulsory statistics modules during their Senior Fresh year along with 20 (or more) ECTS credits of optional statistics modules during each of their sophister years. This gives a total of 60 (or more) ECTS credits in Statistics.
A precise list of the available modules is listed below. Unless indicated otherwise, each module is worth 5 ECTS credits.
For further information, please contact the programme coordinator Dr Athanasios Georgiadis
These modules are compulsory during the Senior Fresh year. This gives a total of 20 ECTS credits in Statistics.
(Semester 2, 5 credits) This module will develop several important ideas in statistical analysis making use of some of the ideas introduced in STU22004. It acts as a bridge to the sophister years by introducing the fundamental ideas that are used in the more advanced statistics modules that will take place then.
(Semester 1 & 2, 10 ECTS) This course is based on developing and solving mathematical models of real life problems. In the first semester, students receive a theoretical introduction to the fundamental elements of a mathematical model. Modelling techniques are taught to solve problems in many domains. In the second semester students are introduced to the concepts, ideas and techniques involved in simulation.
(Semester 1, 5 ECTS) This is a rigorous development of probability theory from an axiomatic foundation, along with some more advanced topics.
(Semester 1, 5 ECTS) Introduction to Forecasting; ARIMA models, data transformations, seasonality, exponential smoothing and Holt Winters algorithms, performance measures. Use of transformations and differences.
(Semester 1, 5 ECTS) Classical multivariate techniques of principal component analysis, clustering, discriminant analysis, k-nearest neighbours, and logistic regression are investigated.
(Semester 1 & 2, 10 ECTS) The aim of the course is to introduce the students to a set of techniques including classification and regression trees, and ensemble methods.
(Semester 1, 5 credits) An introduction to the field of Operations Research.
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