Postgraduate taught 

Data Analytics MSc

Preliminary Mathematics for Statisticians STATS3020

  • Academic Session: 2023-24
  • School: School of Mathematics and Statistics
  • Credits: 0
  • Level: Level 3 (SCQF level 9)
  • Typically Offered: Semester 1
  • Available to Visiting Students: No

Short Description

This course provides students with the mathematical knowledge in Calculus and Linear Algebra required by the courses taught as part of the MSc programmes in Statistics.

Timetable

Two weeks of pre-sessional courses taught in the two weeks immediately preceding the first semester.

Two hours of daily contact time for 10 days.

Assessment

Assessment is by a computer-based test which can be taken on several occasions.

Course Aims

This course aims to provide students with the mathematical knowledge in Calculus and Linear Algebra required by the courses taught as part of the MSc programmes involving Statistics.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Calculate (partial) derivatives and use these to derive properties of functions and approximate functions;

■ Perform (multiple) integration;

■ explain basic concepts from Linear Algebra (such as matrix, vector, linear independence, trace, determinant, matrix inverse, eigenvalue, eigenvector, inner product, orthogonality, quadratic form, spectral decomposition).

use and (if possible) calculate these in practical examples as well as exploit these concepts to derive simple theoretical propositions about vectors and matrices

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.