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Unit information: Numerical Methods and Programming in 2020/21

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Unit name Numerical Methods and Programming
Unit code EASC20041
Credit points 10
Level of study I/5
Teaching block(s) Teaching Block 4 (weeks 1-24)
Unit director Dr. Nick Teanby
Open unit status Not open
Pre-requisites

EASC10007 Computing for Earth Scientists

Co-requisites

N/A

School/department School of Earth Sciences
Faculty Faculty of Science

Description

In this unit students learn how to extract information from numerical data using rigorous numerical and mathematical methods, which will be implemented using the Matlab programming and plotting software. This software is a powerful tool that is used extensively throughout academia and industry.

The skills learnt will be very useful for project and practical work during all degree programmes and for work in diverse careers. The programming skills acquired during this unit build upon and extend those acquired in Computing for Earth Scientists (EASC10007).

Intended learning outcomes

Students will develop:

  • An understanding of the importance of measurement errors when analysing data.
  • An understanding of wide-ranging numerical data analysis techniques.
  • An ability to program in Matlab.
  • An ability to analyse data and model output using Matlab

Teaching details

The unit requires the completion of a series of independent practical exercises delivered via Blackboard. Students are supported through a series of synchronous online, but if possible face-to-face, weekly help and feedback sessions. Students who either begin or continue their studies in an online mode may be required to complete practical work, or alternative activities in person, either during the academic year 2020/21 or subsequently, in order to meet the intended learning outcomes for the unit, prepare them for subsequent units or to satisfy accreditation requirements.

Assessment Details

100% coursework comprising analysis of a scientific dataset and creation of a multi-panel figure incorporating elements of the course ILOs. The figure(s) produced from the data analysis will be combined into a single page PDF for assessment. The Matlab code used to generate the figures will also be submitted for plagiarism checking.

Reading and References

Essential:

  • Trauth. "Matlab recipes for Earth Scientists". 3rd edition, Springer

Recommended (Matlab-based):

Further reading / Reference texts (methods only):

  • Bevington and Robinson. "Data reduction and error analysis for the physical sciences". 3rd edition. McGraw-Hill

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