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Unit information: Multivariate Analysis in 2016/17

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Multivariate Analysis
Unit code MATH30510
Credit points 10
Level of study H/6
Teaching block(s) Teaching Block 1B (weeks 7 - 12)
Unit director Dr. Didelez
Open unit status Not open
Pre-requisites

MATH11300 Probability 1, MATH 11400 Statistics 1, and MATH 11005 Linear Algebra & Geometry

Co-requisites

None

School/department School of Mathematics
Faculty Faculty of Science

Description including Unit Aims

Unit aims

Multivariate analysis is a branch of statistics involving the consideration of objects on each of which are observed the values of a number of variables. Multivariate techniques are used in medicine, physical, environmental, and biological sciences, economics and social science, and of course in many industrial and commercial applications.

A wide range of methods is used for the analysis of multivariate data, both unstructured and structured, and this course will review some of the more common and useful methods, with emphasis on implementation and interpretation.

Relation to Other Units

As with the units Linear Models, Generalized Linear Models, and Time Series Analysis, this course is concerned with developing statistical methodology for a particular class of problems.

Applications will be implemented and presented using the statistical computing environment R (used in Probability 1 and Statistics 1).

Additional unit information can be found at http://www.maths.bristol.ac.uk/study/undergrad/current_units/index.html

Intended Learning Outcomes

Learning Objectives

To gain an understanding of:

  • Dimensional reduction and visualisation of high-dimensional datasets;
  • Structured and unstructured learning approaches, including classification and clustering;
  • Approaches based on notions of similarity/dissimilarity;
  • Implementation in the statistical computing environment R.

Transferable Skills

Self assessment by working examples sheets and using solutions provided.

Teaching Information

Lectures (including both theory and illustrative applications), exercises to be done by students.

Assessment Information

100% Examination.

Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.

Reading and References

Reading and references are available at http://www.maths.bristol.ac.uk/study/undergrad/current_units/index.html

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