Undergraduate Course: Quantitative Methods in Earth Sciences (EASC09047)
Course Outline
| School | School of Geosciences |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 9 (Year 3 Undergraduate) |
Credits | 10 |
| Home subject area | Earth Science |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | 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 Hydrogeology. Furthermore, the course will enhance the student learning experience and ultimately student employability by providing them with important numeracy skills. Such skills are highly valued by employers in different sectors including insurance, finance and exploration but the Earth Sciences curricula are currently deficient in this area. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | Basic calculus and linear algebra |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
1. 1) Ability to write computer programs to read, analyze and plot large datasets
2. 2) An understanding of mathematical techniques for interpreting and relating sequential, spatial and multivariate data commonly used in earth sciences
3. 3) An understanding of uncertainties in quantitative measurements and how they propagate into uncertainties in derived quantities |
Assessment Information
| Mid-term problem set (40%) and final data analysis project (60%) (consideration required of other course work deadlines) |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
1. Programming concepts
data types
reading and writing data
expressions
control constructs
plotting
2. Descriptive statistics
data and errors
measures of central tendency and spread
measures of correlation
probability distributions
3. Analysis of data sequences
examples of sequential data in earth sciences
trend detection
autocorrelation
semivariograms
spectral analysis
4. Analysis of spatial data
examples of spatial data in earth sciences
interpolation
contouring
directional data
5. Analysis of multivariate data
examples of multivariate data in earth sciences
multiple regression
cluster analysis
principal component analysis
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| Transferable skills |
Quantitative modelling of geological processes, analysis and visualization of large datasets, computer programming |
| 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
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| Study Abroad |
Not entered |
| Study Pattern |
10 lectures and 10 ninety-minute computing practicals |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Richard Essery
Tel:
Email: |
Course secretary | Miss Emma Latto
Tel: (0131 6)50 8510
Email: |
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