Studying online
There are now 2 possible online modes for units:
Units with modes Online timetabled and Online flexible are available for any student to self-enrol and study online.
Click on an offering mode for more details.
Unit Overview
- Description
Spatial data, information collected from spatial locations, demands high-level statistical methodology to explore, investigate and make scientific conclusions. Such data arises in a wide range of applied fields such as aerial image processing, astronomy, ecology, engineering, environmental sciences, epidemiology, forestry, mineral prospecting, spatial economics and transportation. Spatial dtatistics, the statistical basis for spatial data science, encompasses statistical analysis of three different types of spatial data: geostatistical data, lattice data and point pattern data. Modeling of these different types of data requires different probabilistic and statistical tools.
This unit begins with a basic introduction to the three types of spatial data and develops some of the statistical tools required to describe and model such data. Then it moves on to in-depth study of a number of topics from the list: spatial stochastic processes, one and higher dimensional point processes, random fields, spatial covariance, variograms, stationarity and non-stationarity, kriging and spatial interpolation, first- and second-order intensity functions, summary functions, spatial models and estimation theory, simulation, spatial regression, spatio-temporal modeling, Bayesian methods in spatial statistics, and analysis of events on linear networks.
The unit will cover real world examples from many different fields. For statistical analysis and simulation the freeware package R will be used.
- Credit
- 6 points
- Offering
(see Timetable) Availability Location Mode Semester 2 UWA (Perth) Face to face - Details for undergraduate courses
- Level 3 option in the Mathematics; Mathematics; Statistics major sequences
- Level 3 elective
- Outcomes
Students are able to (1) distinguish between three different types of spatial data and apply basic statistical tools required conducting inference from such data; (2) demonstrate skill in the use of some of the measures of dependence in spatial processes in analysing and modeling spatial data; (3) demonstrate in-depth knowledge in some of the important topics in spatial statistics; (4) demonstrate knowledge in determining spatial model for some of the spatial data; (5) show skill in simulating some of spatial model using the package R; and (6) demonstrate basic skill in using R for summarising and analysing spatial data.
- Assessment
Indicative assessments in this unit are as follows: (1) in-class tests; (2) assignments; and (3) final examination. Further information is available in the unit outline.
Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.
- Unit Coordinator(s)
- Dr Gopalan Nair
- Unit rules
- Contact hours
- lectures: 3 hours per week
practical class: 1 hour per week from week 2
- The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
- All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
- Visit the Essential Textbooks website to see if any textbooks are required for this Unit. The website is updated regularly so content may change. Students are recommended to purchase Essential Textbooks, but a limited number of copies of all Essential Textbooks are held in the Library in print, and as an ebook where possible. Recommended readings for the unit can be accessed in Unit Readings directly through the Learning Management System (LMS).
- Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.
Face to face
Predominantly face-to-face. On campus attendance required to complete this unit. May have accompanying resources online.
Online flexible
100% Online Unit. NO campus face-to-face attendance is required to complete this unit. All study requirements are online only. Unit is asynchronous delivery, with NO requirement for students to participate online at specific times.
Online timetabled
100% Online Unit. NO campus face-to-face attendance is required to complete this unit. All study requirements are online only. Unit includes some synchronous components, with a requirement for students to participate online at specific times.
Online Restricted
Not available for self-enrolment. Students access this mode by contacting their student office through AskUWA. 100% Online Unit.
NO campus face-to-face attendance. All study and assessment requirements are online only. Unit includes some timetabled activities, with a requirement for students to participate online at specific times. In exceptional cases (noted in the Handbook) students may be required to participate in face-to-face laboratory classes when a return to UWA’s Crawley campus becomes possible in order to be awarded a final grade.
External
No attendance or regular contact is required, and all study requirements are completed either via correspondence and/or online submission.
Off-campus
Regular attendance is not required, but student attends the institution face to face on an agreed schedule for purposes of supervision and/or instruction.
Multi-mode
Multiple modes of delivery. Unit includes a mix of online and on-campus study requirements. On campus attendance for some activities is required to complete this unit.