Preliminary Mathematics for Statisticians (online) STATS3022

  • Academic Session: 2019-20
  • School: School of Mathematics and Statistics
  • Credits: 0
  • Level: Level 3 (SCQF level 9)
  • Typically Offered: Semester 1
  • Available to Visiting Students: No
  • Available to Erasmus Students: No
  • Taught Wholly by Distance Learning: Yes

Short Description

This course provides students with the mathematical knowledge in Calculus and Linear Algebra required by the courses taught as part of the online MSc programme in Data Analytics.

Timetable

The course consists of self-study material and a pass-or-fail test, which can be re-taken repeatedly. The course is pre-sessional and held before the begin of Semester 1.

Requirements of Entry

The course in only available to students on the online MSc in Data Analytics.

A-Level Mathematics (at grade A or better), or equivalent.

Excluded Courses

Preliminary Mathematics for Statisticians

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 online MSc in Data Analytics.

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.