No offerings have been identified for this subject in 2017
SPA409 Introductory Mathematics for Spatial Analysis (8)
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. |
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+ Subject Availability Modes and Location
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.
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Subject information| Duration | Grading System | School: |
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| One session | HD/FL | School of Computing and Mathematics |
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Enrolment restrictions| Must be enrolled in a Graduate Certificate, Graduate Diploma or Masters course |
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Learning OutcomesUpon 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. |
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SyllabusThe 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. |
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The information contained in the 2017 CSU Handbook was accurate at the date of publication: 25 August 2017. The University reserves the right to vary the information at any time without notice.
