On successful completion of this module, students should:

Have a strong grasp of the fundamental statistical ideas of significance tests and confidence intervals, which underpin statistical analysis;

Be able to apply simple statistical methods to practical problems;

Be able to explain why statistical methods are so widely applied in both the natural and social sciences, engineering and business;

Have a sound basis for developing their knowledge of more advanced statistical ideas and methods;

Module Content

Statistical variation;

Parameter estimation;

Statistical tests and their properties;

Design and analysis of simple comparative studies for both binary and continuous variables;

Introductions to Analysis of Variance (ANOVA), regression and contingency tables

The theory will be illustrated by examples from biology, engineering, industry, medicine and the social sciences.

Module Prerequisite

ST1251

Recommended Reading

Extensive handouts (amounting to a course text) will be provided, so the following is for supplemental reading. The book is quite discursive, as it is oriented to a general, rather than a specifically mathematically orientated student readership. D.S. Moore and G.P. MCCabe, Introduction to The Practice of Statistics, Freeman, 5th edition, 2006

Assessment Detail

This module will be examined jointly with ST1251
in a 3-hour examination in Trinity term,
except that those taking just one of the
two modules will have a 2 hour examination. The supplemental exam will consist of 100% exam.