Modiwl ICL-1316:
Mathematics for Computing
Mathematics for Computing (Rhos) 2023-24
ICL-1316
2023-24
School Of Computer Science And Electronic Engineering
Module - Semester 2
10 credits
Module Organiser:
Josh Davies
Overview
Indicative content includes:
- Revision of key numerical skills, such as multiples, factors and primes; powers and scientific notation; ratios; basic algebra such as linear equations and simplification.
- Introduction to how computers store numbers: binary and hexadecimal.
- Introduction to algorithms: construction of algorithms and how they are used in problem solving.
- Boolean logic: simple logic using gates, truth tables and propositional logic.
- Set theory: basic concepts; representation of set data using Venn diagrams; set operations; equivalence; cardinality.
- Matrices: Matrix manipulation and operations, networks, matrix inverses, solving simultaneous equations using matrices.
- Statistics and probability: definition of key terms, combination, permutation, presentation of statistical data, conditional probability, Bayes' theorem, expectation, variance, standard deviation.
Assessment Strategy
-threshold -Equivalent to 40%.Uses key areas of theory or knowledge to meet the Learning Outcomes of the module. Is able to formulate an appropriate solution to accurately solve tasks and questions. Can identify individual aspects, but lacks an awareness of links between them and the wider contexts. Outputs can be understood, but lack structure and/or coherence.
-good -Equivalent to the range 60%-69%.Is able to analyse a task or problem to decide which aspects of theory and knowledge to apply. Solutions are of a workable quality, demonstrating understanding of underlying principles. Major themes can be linked appropriately but may not be able to extend this to individual aspects. Outputs are readily understood, with an appropriate structure but may lack sophistication.
-excellent -Equivalent to the range 70%+.Assemble critically evaluated, relevant areas of knowledge and theory to constuct professional-level solutions to tasks and questions presented. Is able to cross-link themes and aspects to draw considered conclusions. Presents outputs in a cohesive, accurate, and efficient manner.
Learning Outcomes
- Define simple algorithms and utilise problem solving techniques.
- Interpret set theory notation, perform operations on sets and reason about sets.
- Understand how a computer represents numerical data types and how they are applied in Boolean logic.
- Use matrices to solve a range of problems.
- Utilise an appropriate range of techniques in the statistical analysis of sets of data.
Assessment method
Coursework
Assessment type
Crynodol
Description
Individual Problem Set 1 Problem set covering basic mathematical theory, algorithms and boolean logic.
Weighting
20%
Due date
22/04/2024
Assessment method
Coursework
Assessment type
Crynodol
Description
Individual Problem Set 2 Problem Set covering lists, sets, matrices and probability.
Weighting
30%
Due date
04/03/2024
Assessment method
Exam (Centrally Scheduled)
Assessment type
Crynodol
Description
Unseen Examination Controlled assessment covering the whole syllabus.
Weighting
50%