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

This unit discusses advanced statistical models and their inferential procedures, motivated and demonstrated with numerous applied examples. Where appropriate, the underlying general concepts and basic theory are discussed, within either a Frequentist or Bayesian framework, or both. Data sets are analysed using the statistical package R. Topics are selected from, but are not limited to: categorical data analysis, survival analysis, longitudinal data analysis, multilevel models, missing data analysis, (generalised) linear mixed models, non-linear regression, life/failure time analysis, time-to-event data analysis, predictive modelling, non-linear regression analysis, Bayesian data analysis, time series analysis, high-dimensional data, functional data analysis, likelihood modelling, actuarial statistics, multivariate statistical methods, non-parametric statistics and spatial statistics.

Credit
6 points
Offering
(see Timetable)
AvailabilityLocationMode
Semester 1UWA (Perth)Face to face
Details for undergraduate courses
  • Level 4 core unit in the 4 specialisation in the major sequence
  • Level 4 elective
  • Honours option in Mathematics and Statistics [Bachelor of Science (Honours)]
Outcomes

Students are able to (1) appropriately apply techniques from the chosen topics to real-world problems and communicate results in a logical and coherent fashion to others; (2) apply statistical reasoning in general to analyse the essential structure of problems in various fields of human endeavour; (3) extend their knowledge of statistical modelling techniques and adapt known solutions to different situations; and (4) undertake continuous learning in statistical modelling and inference, being aware that an understanding of fundamentals is necessary for effective application.

Assessment

Indicative assessments in this unit are as follows: (1) end-of-semester examination and (2) in-semester tests and assignments. 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 Nazim Khan
Unit rules
Prerequisites

Course Enrolment in
the HON-MTHST Mathematics and Statistics [Honours]
or the MJD-CDSDM Computing and Data Science major
and STAT3062 Statistical Science
or STAT3401 Advanced Data Analysis
and STAT3064 Statistical Learning
Contact hours
3-hours per week
  • 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.