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unitinfo
This page provides helpful information about many coursework units offered by
Computer Science and Software Engineering
in 2023.
The information here is not official -
for official information please see the
current UWA Handbook.
Instead, it will help students to prepare for their future units,
before the beginning of each semester,
and before they have access to
UWA's
Learning Management System (LMS).
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About the unit STAT3064 Statistical Learning (2nd semester 2023)
Unit 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.
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..
Unit coordinator:
Unit homepage:
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Unit is offered in these majors and courses:
Indicative weekly topics:
| week 1 |
Into to Statistical Data Science/Statistical Learning |
| week 2 |
Principal Component Analysis (PCA): part I |
| week 3 |
Principal Component Analysis (PCA): part II |
| week 4 |
Canonical Correlation Analysis (CCA) |
| week 5 |
Canonical Correlation Analysis (CCA), part II and Factor Analysis (FA) |
| week 6 |
Factor Analysis (FA) part II |
| week 7 |
Agglomerative Hierarchical Clustering |
| week 8 |
k-Means Clustering |
| week 9 |
A Case Study and More Cluster Analysis |
| week 10 |
Linear Discriminant Analysis (LDA) |
| week 11 |
Cross-Validation and Logistic Regression |
| week 12 |
Logistic Regression part II |
Indicative assessment:
Quizzes, Assignments, Practical Test and Final Exam
Useful prior experience and background knowledge:
STAT2401 and STAT2402
Useful prior programming and software experience:
Operating system(s) used in this unit:
Different units will use different operating systems for their teaching - for in-class examples, laboratory exercises, and programming projects.
If an operating system is REQUIRED, it will be used when marking assessments.
ANY reasonable platform
This information last updated 2:47pm Sun 23rd Apr 2023
