Module description
Syllabus
Elementary combinatorial analysis, Definition of probability, Unions and intersections - Statistical Independence, Conditional probability, Bayes’s theorem, Random variables (discrete and continuous), Probability distributions (Binomial, Poisson, Normal, Gamma), Covariance and correlation, Independent variable and the law of large numbers, Central limit theorem, Sampling distributions (Normal, Students-t), Estimators, Confidence intervals, Hypothesis testing.
Assessment details
Written examination and class tests.
Exercises or quizzes will be set each week to be handed in the following week. These problems will be discussed in the tutorials and solutions will be available.
Educational aims & objectives
The aim of the module is to introduce the basic concepts and computations of the theory of probability and the theory of statistical analysis and inference.
Teaching pattern
Three hours of lectures and one hour of tutorial per week throughout the term
Suggested reading list
Indicative reading list - link to Leganto system where you can search with module code for lists