3A Mathematics for Social Scientists III
Edward Codling, University of Essex
5 - 16 August (two week course / 15 hrs)
Detailed Course Outline [PDF]
Mathematics for Social Scientists is offered throughout the six weeks with teaching scheduled daily before other courses. If taken in conjunction with another course, there is no extra charge.
Course Content
This component of the course focuses on solving systems of linear equations by Gaussian elimination; inverse matrices and singularity; vector spaces and subspaces; linear dependence, dimension, and rank; matrix eigenvalues and eigenvectors. It also considers the application of these topics to the linear regression problem and to the principal components problem.
Course Objectives
To provide participants with the essentials of linear algebra required for the study of multivariate analysis. Emphasis is placed on the relationship between the algebra and geometry of vector spaces.
Course Prerequisites
For participants who have not taken the second half of Mathematics for Social Scientists, Part 2, some familiarity with matrix arithmetic is required.
Reading
For a review of the concepts listed in the prerequisites we recommend the Matrices and Vectors quick reference leaflets which can be found by following the leaflets link from maths centre. Note that the site also has learning resources available for these and other basic mathematical topics
Haeussler, E.F., R.S. Paul, and R. Wood. 2004: Introductory Mathematical Analysis for Business, Economics, and the Life and Social Sciences. Prentice Hall.