Undergraduate Course: Quantitative Methods in Earth Sciences (EASC09047)
Course Outline
| School | School of Geosciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 9 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | Quantitative and computational methods are widely used by industry and academic researchers in the Earth Sciences. This course will look at the many types of quantitative data that are encountered in Earth Sciences, how they can be interpreted and how they can be presented. Theory in lectures will be backed up by practical classes which give an introduction to programming in Python, a widely-used open source language with powerful capabilities for scientific computing. Students will get to see the relevance of quantitative methods through the use of data from current research in the School. Numerical methods will be illustrated with examples of their use within research codes and professional software tools. The theory will aid understanding of quantitative concepts in other Honours courses such as Structural Geology, Chemical Geology and Hydro-geology. Numeracy and programming skills taught in this course are highly valued by employers in many sectors, including insurance, finance and exploration. |
| Course description |
1. Programming concepts
Data types; reading and writing data; expressions; control constructs; and plotting.
2. Descriptive statistics
Data and errors; measures of central tendency and spread; measures of correlation; and probability distributions.
3. Analysis of data sequences
Examples of sequential data in earth sciences; trend detection; autocorrelation; semivariograms; and spectral analysis.
4. Analysis of spatial data
Examples of spatial data in earth sciences; interpolation; and contouring; directional data.
5. Analysis of multivariate data
Examples of multivariate data in earth sciences; multiple regression; cluster analysis; and principal component analysis.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | Basic calculus and linear algebra |
Course Delivery Information
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| Academic year 2015/16, Available to all students (SV1)
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Quota: 100 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
98 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Written Exam: 0%, Course Work: 100 %, Practical Exam: 0%.
Mid-term Test (40%)
An online set of questions relating to lecture and practical material from Weeks 1 to 4 of the course, to be completed on Learn during the practical class in Week 5 (1.5 hours).
Final assignment on programming and data analysis (60%)
The assignment will be to write a Python program that will read, plot and analyse a supplied earth science dataset.
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| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Write computer programs to read, analyse and plot large datasets.
- Understand mathematical techniques for interpreting and relating sequential, spatial and multivariate data commonly used in earth sciences.
- Understand uncertainties in quantitative measurements and how they propagate into uncertainties in derived quantities.
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Reading List
Davis, JC. Statistics and data analysis in geology. Wiley
McKillup, S, and Dyar, MD. Geostatistics explained: an introductory guide for earth scientists. Cambridge |
Additional Information
| Graduate Attributes and Skills |
Quantitative modelling of geological processes, analysis and visualization of large datasets, computer programming |
| Additional Class Delivery Information |
Lectures on Tuesdays at 12:10-13:00, Weeks 1-11.
Practicals on Fridays at 14:10-16:00, Weeks 1-11. |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Richard Essery
Tel:
Email: |
Course secretary | Mr Ken O'Neill
Tel: (0131 6)50 8510
Email: |
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