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.

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Unit Overview


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.

6 points
(see Timetable)
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

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.


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 Nazim Khan
Unit rules
Mathematics Applications ATAR
or MATH1720 Mathematics Fundamentals
or MATX1720 Mathematics Fundamentals or equivalent
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
Practical Classes: 2-hours per week
Laboratories: 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.
  • Unit readings, including any essential textbooks, are listed in the unit outline for each unit, one week prior the commencement of study. The unit outline will be available via the LMS and the UWA Handbook one week prior the commencement of study. Reading lists and essential textbooks are subject to change each semester. Information on essential textbooks will also be made available on the Essential Textbooks. This website is updated regularly in the lead up to semester so content may change. It is recommended that students purchase essential textbooks for convenience due to the frequency with which they will be required during the unit. A limited number of textbooks will be made available from the Library in print and will also be made available online wherever possible. Essential textbooks can be purchased from the commercial vendors to secure the best deal. The Student Guild can provide assistance on where to purchase books if required. Books can be purchased second hand at the Guild Secondhand bookshop (second floor, Guild Village), which is located on campus.
  • 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.