This module is not currently running in 2024 to 2025.
This module will introduce the basic concepts of probability and statistics, with applications to a variety of topics illustrated with real data. The techniques that are discussed can be used in their own right to solve simple problems, but also serve as an important foundation for later, more advanced, modules. After dealing with key ideas in probability theory, the module will cover descriptive statistics, before moving on to statistical inference - the science of drawing conclusions from data. A brief introduction to statistical computing will be included. Outline syllabus includes: Concepts and axioms of probability; marginal, conditional and joint probabilities; Bayes' theorem; discrete and continuous random variables; expectation; common distributions; numerical summaries of data; sampling distributions; point estimation; interval estimation and hypothesis tests; association between variables; goodness of fit.
Marks on this module can count towards exemption from the professional examination CT3 of the Institute and Faculty of Actuaries. Please see http://www.kent.ac.uk/casri/Accreditation/index.html for further details.
48, consisting of lectures, classes and computer sessions
Examination (90%) and coursework (10%)
GM Clarke & D Cooke: A Basic Course in Statistics (5th ed. Arnold, 2004) (B)
S Ross: A First Course in Probability (4th ed. Prentice Hall, 1994)
J Crawshaw & J Chambers: A Concise Course in A-Level Statistics, with Worked Examples (3rd ed. Stanley Thornes, 1994)
DV Lindley & WF Scott: New Cambridge Elementary Statistical Tables (2nd ed. C.U.P., 1995) (E)
See the library reading list for this module (Canterbury)
The intended subject specific learning outcomes
On successful completion of this module students will:
a) have gained an understanding of the basic concepts of probability and statistics;
b) have established a framework of core statistical material relevant to their degree programme, and which is also appropriate for later statistics modules students may need to study as part of their degree;
c) be proficient in the main statistical ideas and techniques introduced in the course;
d) have some appreciation of ways of examining data, both at the exploratory stage through graphical representations and numerical summaries, and more formally through techniques of statistical inference;
e) be able to handle and analyse data using the statistical package MINITAB;
f) have some appreciation of how statistics is used in practice.
g) have an appreciation of how the statistical procedures covered are derived and their validity
The intended generic learning outcomes
Students who successfully complete this module will:
a) have begun to develop a logical, mathematical approach to solving problems;
b) have enhanced their ability to work with relatively little guidance;
c) have gained organisational and study skills;
d) be able to use information technology for data analysis and presentation.
On successful completion of the module, students will also have improved their key skills in written communication, numeracy, computing and problem solving.
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