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

Many real-world problems involve analysing data sets that are not normally distributed. For example, binomial data in the form of presence/absence recordings, Poisson data measured as counts of rare events such as car accidents, Gamma data for measurements of rainfall and Weibull data for the expected lifetimes of machinery. This unit provides experience in analysing such observations. The majority of the unit concentrates on the presentation and analysis of such data sets. Generalised Linear Models (GLMs) are used to incorporate explanatory variables into the analyses. In developing these skills students are trained in an appropriate statistical software package. The unit also provides a rudimentary understanding of probability and statistics necessary for applying the likelihood theory for estimating these models.

Credit
6 points
Offering
(see Timetable)
AvailabilityLocationMode
Semester 2UWA (Perth)Face to face
Details for undergraduate courses
  • Level 2 core unit in the Data Science; Computing and Data Science; Human Sciences and Data Analytics; Statistics major sequences
  • Level 2 elective
Outcomes

Students are able to (1) demonstrate their knowledge of fundamental concepts in probability and statistics; (2) apply statistical models to real-world problems for data that are not normally distributed; (3) use computer package(s) for fitting such models to data; and (4) communicate the results of these analyses effectively to non-statisticians.

Assessment

Indicative assessments in this unit are as follows: (1) two assignments and (2) a 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 Darfiana Nur
Unit rules
Prerequisites
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals
or MATX1720 Mathematics Fundamentals or equivalent
or
Enrolment in
62530 Master of Data Science
Advisable prior study
STAT1400 Statistics for Science
Or STAT1520 Economic and Business Statistics
Contact hours
Lectures: 3-hours per week
Computer Labs: 2-hours per week
Workshops: 1-hour 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.