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.

View all online units

Unit Overview

Description

This unit introduces fundamental concepts and contemporary methods of Statistical Learning – both supervised and unsupervised learning approaches, and shows how to apply these methods to different data science domains (e.g. physical sciences, medical and biological sciences, engineering, business and social sciences). Focus will be on the interaction between methods and data, on learning to choose suitable methods of data analysis for particular data and on interpreting the results. Statistical computing (including R and/or Matlab) will form an essential part of this unit.

Credit
6 points
Offering
(see Timetable)
AvailabilityLocationMode
Semester 2UWA (Perth)Face to face
Details for undergraduate courses
  • Level 3 core unit in the Data Science; Computing and Data Science; Human Sciences and Data Analytics major sequences
  • Level 3 option in the Mathematics; Mathematics; Statistics major sequences
Outcomes

Students are able to (1) explain the basic concepts and methods of Statistical Learning; (2) choose appropriate supervised or unsupervised approaches for a particular data set; (3) critically assess the suitability of the approach for a particular data set; (4) use modern programming languages to analyse data; (5) interpret results of multivariate data analysis; and (6) communicate results of multivariate data analysis..

Assessment

Indicative assessments in this unit are as follows: (1) assignment; (2) in-semester test; and (3) exam. 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
Enrolment in
MJD-CDSDM Computing and Data Science
or MJD-MTHST Mathematics and Statistics
or MJD-DATSC Data Science
or MJD-HSDEM Human Sciences and Data Analytics
and
STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or
STAT2062 Fundamentals of Probability with Applications
or STAT2063 Probabilistic Methods and their Applications
Incompatibility
STAT4067 Applied Statistics and Data Visualisation
and STAT5061 Statistical Data Science
Advisable prior study
CITS2402 Introduction to Data Science
Contact hours
Lectures: 2-hours per week
Laboratory: 2-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.

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.