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School of Mathematics

# MATH10002 - 2009/2010

General Information
• Title: Mathematical Workshop
• Unit code: MATH10002
• Credits: 10
• Prerequisites: A-Level Mathematics, MATH10141 Probability and Statistics 1
• Co-requisite units: None
• School responsible: Mathematics
• Members of staff responsible: Dr. Louise Walker and Dr. Peter Foster
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## Specification

### Aims

The aims of this course unit are to help students

• use Matlab to solve mathematical problems;
• develop a knowledge of basic statistical ideas which build on the ideas in probability studied in MATH10141;
• develop practical statistical skills.

### Brief Description of the unit

The first half of the course will give an introduction to the mathematical software package Matlab. In the final six weeks of the course students will study introductory statistics and use Minitab to work on practical applications of statistical theory.

### Learning Outcomes

On successful completion of this course unit students will be able to

• use Matlab to solve equations, plot functions and perform matrix calculations;
• understand introductory statistics;
• use Minitab to analyse statistical data.

### Future topics requiring this course unit

The approaches to problem solving with be beneficial in later Mathematical study. The statistics content is required for MATH20802 Statistical Methods and MATH20812 Practical Statistics 1.

### Content

• Weeks 1 to 5: Introduction to Matlab and Numerical Methods;
• Weeks 6 to 11: Statistics lectures and laboratory:
• Population and samples, sample statistics;
• Sampling distributions, how good are sample statistics as estimators of population parameters?
• Likelihood and maximum likelihood estimators for discrete variables;
• Confidence intervals;
• Hypothesis testing.

### Textbooks

• G M Clarke and D Cooke, A Basic Course in Statistics (Fourth Edition) Oxford University Press, 1998;
• Desmond J. Higham and Nicholas J. Higham, MATLAB Guide, Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, Second edition 2005.

### Teaching and learning methods

One lecture per week in weeks 1-5 and two lectures per week in weeks 6-11. One hour workshop per week. In addition students are expected to do at least five hours private study each week on this course unit.

### Assessment

Weeks 1-5 (MATLAB): continuous assessment (30%).

Weeks 6-11 (Statistics): two projects (worth 35% of the marks for the Statistics component), an in-class test (worth 25% of the marks) and attendance and work at the computing laboratories (worth 10% of the marks).

## Arrangements

Online course materials are available for this unit.