Statistics is the study of uncertainty, which arises in all aspects of life. Statistical theory and methods are fundamental to our understanding of such uncertainty, and are an increasingly sought after skill. This module presents a parallel development of statistical theory and methods, building on the introductory material in the module Probability, Data and Statistics. Topics covered include classical linear models, with an introduction to the analysis of variance; basic methods for handling discrete data; further work in the theory of probability distributions; and some aspects of the theory of estimation and hypothesis testing. In the computing sessions, a statistical package is used to illustrate the application of statistical methods to the analysis of some typical data sets.
Learning Outcomes
By the end of the module students should be able to:
Demonstrate a basic understanding of the principles of statistical inference
Handle simple problems in the distributional calculus;
Identify standard situations to which statistical models apply
Build statistical models and use them for the analysis of data;
Demonstrate fluency with a standard statistical package.
Assessment
Assessment Methods & Exceptions
Assessment:
2hr examination (80%) In-course assessment (20%) (including a variety of assessment possibly including problem sheets, class tests, online quizzes and group projects)
