MAS2502 : Introduction to Computing and Problem Solving (Inactive)
- Inactive for Year: 2024/25
- Module Leader(s): Dr George Stagg
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
| European Credit Transfer System | |
Aims
To introduce the mathematical and statistical computer environments Python and R. To promote familiarity with both these environments for standard mathematical and statistical operations, and to work towards the ideas of coding user-defined functions, and further towards programming aimed at solving more substantial problems.
To promote some element of independent thinking and critical appraisal by linking the computational experience to the tackling of unfamiliar problems. Through these aims, to prepare for computational/problem solving needs in Applied and Statistics modules taken in Semester 2 and in Stage 3.
Module summary
Computing methods are of great use in a wide range of applications of [pure and] applied mathematics and statistics. This module will introduce and develop familiarity with mathematical/statistical computing, relate this to problem solving techniques based on independent thinking, and develop the ability to apply such methods independently, towards specific goals in mathematical and statistical study and applications.
Outline Of Syllabus
Use of Python and R for mathematical and statistical computing. Getting started, input and output, data types, plotting and simple calculations, control statements, functions, random variables.
Individual and group problems on existing mathematical and statistical knowledge (such as calculus, sequences and series, single value functions, curve sketching and simple numerical analysis, linear algebra, matrix manipulations, permutations and combinations, simulation of random variable, transformations and sums of random variables, sample means, variances, and the behaviour of these when considered as random variables).
Mathematical problems and puzzles from logic, number theory, geometry, algebra, probability, strategy.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 11 | 1:00 | 11:00 | Formal lectures |
| Guided Independent Study | Assessment preparation and completion | 2 | 8:00 | 16:00 | Revision for class tests |
| Scheduled Learning And Teaching Activities | Practical | 9 | 2:00 | 18:00 | Computer practicals |
| Scheduled Learning And Teaching Activities | Practical | 2 | 2:00 | 4:00 | Class tests (80 minute test within two hour practical session) |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 12 | 0:10 | 2:00 | Office hours |
| Guided Independent Study | Independent study | 1 | 21:00 | 21:00 | Studying, practising and gaining understanding of course material |
| Guided Independent Study | Independent study | 3 | 4:00 | 12:00 | Review of and class tests and team project |
| Guided Independent Study | Independent study | 1 | 16:00 | 16:00 | Preparation for team project |
| Total | 100:00 |
Teaching Rationale And Relationship
Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Practicals are used to help the students to develop their programming skills but also afford an opportunity to develop the students’ abilities at applying the theory to solving problems. Office hours (two per week) provide an opportunity for more direct contact between individual students and the lecturer: a typical student might spend a total of one or two hours over the course of the module, either individually or as part of a group.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Written exercise | 1 | M | 30 | Team project |
| Computer assessment | 1 | M | 35 | PC test 1 (80 mins, in-class) |
| Computer assessment | 1 | M | 35 | PC test 2 (80 mins, in-class) |
Assessment Rationale And Relationship
The team project allows the students to develop their problem solving techniques and to practise the methods learnt in the module. It also allows the assessment of the computational skills acquired by the students. The PC tests allow the students to assess their progress with the material. They both allow feedback to the students and so act as formative as well as summative assessment. The team project is a written report which will be marked by a module lecturer with one third of the group mark weighted by means of peer assessment.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- MAS2502's Timetable