STAT4064 Applied Predictive Modelling

6 points
(see Timetable)

If this unit does not have an online alternative, then students who are presently unable to enter Western Australia and whose studies would be delayed by an inability to complete this unit, should contact the unit coordinator (details given on this page) to ascertain, on an individual case-by-case basis, if alternate arrangements can be made to support their study in this unit.

Semester 2UWA (Perth)Face to face Predominantly face-to-face. On campus attendance required to complete this unit. May have accompanying resources online.
Details for undergraduate courses
  • Honours option in Mathematics and Statistics [Bachelor of Science (Honours)]
This unit covers a set of tools for modelling, understanding and predicting from complex data sets. The tools are selected from topics that are a natural blend of statistics and machine learning, and are motivated and demonstrated with applied examples. The underlying general concepts and basic theory are discussed at a level accessible to students. Data sets are analysed using the statistical package R and the unit provides an introduction to this software. Topics are selected from statistical inference, linear regression, model selection, classification, resampling methods, tree-based methods, support vector machines and machine learning.
Students are able to (1) apply appropriate techniques from the above topics to real world data and communicate results in a logical and coherent fashion; (2) apply statistical reasoning in general to analyse the essential structure of problems in various fields of data science; (3) extend students' knowledge of statistical modelling techniques and adapt known solutions to different situations; and (4) undertake continuous learning in statistical predictive modelling and inference, being aware that an understanding of fundamentals is necessary for effective application.
Indicative assessments in this unit are as follows: (1) tests and assignments and (2) a final examination. Further information is available in the unit outline.

Supplementary assessment is not available in this unit.
Unit Coordinator(s)
Professor Inge Koch
Unit rules
STAT2401 Analysis of Experiments (ID 390) or STAT2402 Analysis of Observations (ID 389) or STAT2062 Fundamentals of Probability with Applications (ID 5019)
Advisable prior study:
(STAT2401 Analysis of Experiments (ID 390) and STAT2402 Analysis of Observations (ID 389)) orSTAT2062 Fundamentals of Probability with Applications (ID 5019)
Contact hours
lectures: 2 hours per week; computer laboratories: 2 hours per week
Unit will be changed from Semester 2 to Semester 1 from 2022.
  • 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.