MAT-10057 - Introduction to Probability and Statistics
Coordinator: Paul J Truman Room: MAC2.16 Tel: +44 1782 7 33246
Lecture Time: See Timetable...
Level: Level 4
Credits: 15
Study Hours: 150
School Office: 01782 733075

Programme/Approved Electives for 2022/23


Available as a Free Standing Elective






Barred Combinations


Description for 2022/23

This module introduces students to the fundamental mathematical language and concepts used in the study of chance and uncertainty, and in the analysis, interpretation, and presentation of data. This lays the foundations for subsequent modules in these areas, and their applications in other areas of the natural and social sciences.

Intended Learning Outcomes

model simple experiments using probability theory and perform standard probability calculations, including working with conditional probabilities;: 1
recall, select, and apply appropriate standard methods to summarise data;
: 2
differentiate between common types of data, and display them appropriately;: 2
apply simple formal statistical techniques and interpret the results.: 2

Study hours

40 Scheduled teaching hours comprises 20 hours lectures and 20 hours exercise classes / case study examples.
110 hours independent study, comprises 20 hours preparation for, and completion of, online exercises, 60 hours consolidation of lecture material, 30 hours preparation for, and completion of, the final assessment.

School Rules


Description of Module Assessment

1: Assignment weighted 40%
Probability exercises
Approximately 3 sets of online exercises focussing on the probability portion of the syllabus. Where possible, these will be assessed via automated methods such as MCQ's/MapleTA, so that students can receive immediate feedback. More involved questions will be marked by hand, and feedback provided in the usual manner.

2: Unseen Case - Process weighted 60%
Case study under controlled conditions
Case study to be completed in 2 hours under controlled conditions. Students will be asked to analyse previously unseen data set(s), describe and display their findings, and draw conclusions in the context of the case study. Credit will be given for well justified and accurate application of appropriate techniques, and clear interpretation and communication of conclusions.