Mathmatical Foundations in the Planetary and Geological Sciences EARTH5023
- Academic Session: 2025-26
- School: School of Geographical and Earth Sciences
- Credits: 10
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 1
- Available to Visiting Students: Yes
- Collaborative Online International Learning: No
- Curriculum For Life: No
Short Description
In this course we will introduce fundamental mathematical techniques needed for advanced study in the space, planetary and geological sciences. This is intended short course to address knowledge gaps in students undertaking graduate level studies or research in the above scientific disciplines. This course will cover the topics of integral and differential calculus, basics statistics, and linear algebra. Applications of these methods to problems in the space and planetary sciences will be demonstrated though the development of interactive coding exercises linking symbolic computation to numerical methods.
Timetable
Lectures twice per week with practical workshop
Requirements of Entry
None
Excluded Courses
None
Co-requisites
None
Assessment
Students will develop a portfolio evidencing their development in coding and solving numerical problems in the planetary and space sciences.
Additionally, there will be weekly quizzes on the topics covered as well as set exercises that will be assessed.
Course Aims
The aim of this course is to increase students understanding of fundamental mathematical techniques required for mission planning, statistical analysis and remote sensing analysis
Intended Learning Outcomes of Course
By the end of this course students will be able to:
■ Symbolically present planetary and space science questions invoking mathematical concepts such as functions, derivatives, integrals, and basic statistics.
■ Code visualisation of numerical relationships and transformations to understand quantitative relationships in the planetary sciences.
■ Solve linear equations describing physical problems as matrices in code to numerically compute quantities including rates of change and distances as well as perform statistical tests.
■ Develop a numerical model for a set of observations using least squares fit using the coding tools presented.
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.