SPA409 Introductory Mathematics for Spatial Analysis (8)
CSU Discipline Area: Spatial Science (SPASC)
Duration: One session
Abstract:
This subject provides an introduction to the basic mathematical and statistical techniques required for spatial analysis applications in GIS, image analysis and remote sensing.
+ Subject Availability Modes and Locations
No offerings have been identified for this subject in 2013.Continuing students should consult the SAL for current offering details prior to contacting their course coordinator: SPA409
Where differences exist between the handbook and the SAL, the SAL should be taken as containing the correct subject offering details.
Enrolment restrictions:
Must be enrolled in a Graduate Certificate, Graduate Diploma or Masters course
Objectives:
Upon successful completion of this subject, students should:
Understand the mathematical and statistical concepts that underpin many procedures used in the fields of GIS, image processing and remote sensing;
Be able to apply mathematical and statistical techniques to assist in the solution of a range of probems in spatial analysis.
Syllabus:
The subject will cover the following topics:
Introduction to differential calculus: historical background, functions, limits, slope of a tangent, derivative, stationary points, applications of differentiation; Introduction to integral calculus: indefinite integrals, approximate areas, definite integrals, applications of integration; Introduction to vectors and matrices: elementary matrix operations, determinant, inverse, solutions of systems of linear equations; Introduction to linear algebra: linear maps, eigenvectors, eigenvalues, diagonalization of a matrix; Simple probability concepts: complement, addition rule, product rule; Representation of data - histogram, stem-and-leaf plot, boxplot, scatterplot; Descriptive statistics: mean, standard deviation, variance, covariance, correlation and standardised values; The normal distribution with applications; Other distributions including chi-square, F and multivariate normal distributions; Introduction to regression: simple linear regression.
The information contained in the 2013 CSU Handbook was accurate at the date of publication: 24 April 2013. The University reserves the right to vary the information at any time without notice.