ST116 Mathematical Techniques
ST11612 Mathematical Techniques
Introductory description
This module runs in term 1 and is core for students with their home department in Statistics. It is NOT available for other students.
Module aims
Students will develop a deeper understanding of mathematical concepts and relations using problem solving techniques such as visualisation and exploration of patterns. By learning to express mathematical ideas clearly and precisely students will further deepen their understanding and enhance their mathematical reasoning and communication skills.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
An introduction to mathematical thinking and writing covered through examples and applications from the areas such as logic, sets, functions, combinatorics, and discrete probability.
Learning outcomes
By the end of the module, students should be able to:
 Use mathematical notation accurately.
 Apply a selection of mathematical problem solving techniques.
 Visualise mathematical concepts.
 Understand and construct a coherent, rigorous mathematical argument.
Indicative reading list
K. Houston (2009) "How to think like a Mathematician", Cambridge University Press.
L.Alcock (2013) "How to study for a mathematics degree ", Oxford University Press.
K.Devlin (2003) "Sets, Functions, and Logic: an Introduction to Abstract Mathematics",
Chapman & Hall/CRC.
Ross, S. (2014). A first course in probability. Pearson.
View reading list on Talis Aspire
Subject specific skills
 familiarity with basic concepts in the foundational core of mathematics and key ideas in discrete probability theory and the ability to perform routine calculation and manipulation within this basic body of knowledge;
 familiarity with basic mathematical approaches to problem solving and the ability to justify chosen solution strategies;
 an appreciation of the structure of logical mathematical arguments and the ability to develop and reproduce simple mathematical arguments and proofs with a degree of clarity and accuracy;
 the ability to persist with simple, nonroutine mathematical problems.
Transferable skills
 the ability to use a learning style and pace appropriate for first year university and to appreciate their strengths and weaknesses as learners;
 the ability to work within a structured environment with some degree of autonomy;
 problemsolving, numerical and analytical skills in routine, possibly abstract, contexts and the ability to communicate appropriate solutions with a degree of clarity and accuracy;
 timemanagement and organisational skills;
 decisionmaking skills in standard, welldefined contexts.
Study time
Type  Required 

Lectures  24 sessions of 1 hour (20%) 
Tutorials  8 sessions of 1 hour (7%) 
Private study  64 hours (52%) 
Assessment  26 hours (21%) 
Total  122 hours 
Private study description
Weekly revision of lecture notes and materials, wider reading and practice exercises, working on problem sets and preparing for examination.
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Assessment group D2
Weighting  Study time  

Problem Sets  20%  24 hours 
There will be weekly problem sets, of which up to five will contribute towards your module mark. 

Online Examination  80%  2 hours 
The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade. ~Platforms  Moodle

Assessment group R1
Weighting  Study time  

Online Examination  Resit  100%  
The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade.

Feedback on assessment
You will hand in answers to selected questions on the weekly problem sheets. Your work will be marked and returned to you in the tutorial taking place the following week when you will have the opportunity to discuss it.
Solutions and cohort level feedback will be provided for the examination and the results for the exam in December will be available by the end of Week 10 of Term 2.
Courses
This module is Core for:
 Year 1 of USTAG302 Undergraduate Data Science
 Year 1 of USTAG304 Undergraduate Data Science (MSci)
 Year 1 of USTAG300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
 Year 1 of USTAG1G3 Undergraduate Mathematics and Statistics (BSc MMathStat)
 Year 1 of USTAGG14 Undergraduate Mathematics and Statistics (BSc)
 Year 1 of USTAY602 Undergraduate Mathematics,Operational Research,Statistics and Economics
Catalogue 
Additional Information 
Resources 
Feedback and Evaluation 
Grade Distribution 
Timetable 
This module ended in 2020/21 and this information is only relevant to students with reassessments.