STAT3064 Statistical Learning

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 major sequence
  • Level 3 option in the Mathematics and Statistics major sequence
  • The area of knowledge for this unit is Mathematical and Physical Sciences
Content
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.
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.

Supplementary assessment is not available in this unit except in the case of a bachelor's pass degree student who has obtained a mark of 45 to 49 overall and is currently enrolled in this unit, and it is the only remaining unit that the student must pass in order to complete their course.
Unit Coordinator(s)
Professor Inge Koch
Unit rules
Prerequisites:
STAT2401 Analysis of Experiments
or
STAT2062 Fundamentals of Probability with Applications
and
MATH1720 Mathematics Fundamentals
or
MATH1011 Multivariable Calculus
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.
  • Books and other material wherever listed may be subject to change. Book lists relating to 'Preliminary reading', 'Recommended reading' and 'Textbooks' are, in most cases, available via the Booktopia Textbook Finder, which has the functionality to search by course code, course, ISBN and title, and may also be posted or available at the appropriate school's administrative offices. Where texts are listed in the unit description above, an asterisk (*) indicates that the book is available in paperback.