## MA1MSP-Mathematical and Statistical Programming

Module Provider: Mathematics and Statistics
Number of credits: 20 [10 ECTS credits]
Level:4
Terms in which taught: Autumn / Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites: MA1CA Calculus MA1LA Linear Algebra MA1FM Foundations of Mathematics ST1PS Probability and Statistics
Modules excluded:
Module version for: 2017/8

Module Convenor: Dr Fazil Baksh

Summary module description:

This module introduces students to the valuable skill of programming with clear links to applications in mathematics and statistics. Programming in Matlab, R and SAS will be covered. Examples from co-requisite modules, in both mathematics and statistics, will be used to illustrate various programming techniques.

Aims:

• To develop basic and intermediate programming skills in the context of other modules being taken;

• To introduce the concepts of program design;

• To introduce a variety of computer languages relevant to mathematics and statistics;

• To introduce good programming practice in the structure, maintenance and in-program documentation of the code;

• To be able to display results visually using graphics capabilities of the languages;

• By the end of the module students should be able to dissect a given problem into an algorithm suitable for programming in a variety of languages.

Assessable learning outcomes:

• Students will be able demonstrate the ability to transfer mathematical and statistical problems into programs across a variety of different programming languages;

• Students will be able to demonstrate good programming practice in structure, maintenance and documentation of code;

• Student will be able to display results visually using graphics capabilities of the languages.

• Students will further develop their transferable skills in the area of programming for the mathematical and statistical sciences;

• This module will support the learning process in the co-requisite modules.

Outline content:

• An introduction to the concept of programming, including top-down design;

• Various mathematical and statistical concepts will be analysed and appropriate programming techniques applied to facilitate solution and understanding;

• A variety of scientific programming languages will be introduced, including Matlab and R, in which developed algorithms will be implemented.

Brief description of teaching and learning methods:
Lectures, computer labs, self-guided study as well as summative and formative assignments. Worksheets and self- evaluation /feedback mechanisms.

Contact hours:
 Autumn Spring Summer Lectures 8 7 Practicals classes and workshops 12 13 Guided independent study 80 80 Total hours by term 100.00 100.00 Total hours for module 200.00

Summative Assessment Methods:
 Method Percentage Set exercise 100

Other information on summative assessment:
A number of programming assignments during the course of the two terms.

Formative assessment methods:
A number of non-assessed programming exercises and worksheets to illustrate the material being taught, resulting in detailed feedback to enhance programming skills.

Penalties for late submission:
The Module Convenor will apply the following penalties for work submitted late, in accordance with the University policy.

• where the piece of work is submitted up to one calendar week after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for the piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

• The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Length of examination:
Not applicable.

Requirements for a pass:

A mark of 40% overall.

Reassessment arrangements:

Alternative coursework.