- Code STAT3040
- Unit Value 6 units
- Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
- ANU College ANU College of Business and Economics
- Course subject Statistics
- Areas of interest Actuarial Studies, Statistics
- Academic career UGRD
- Mode of delivery In Person
First Semester 2021
See Future Offerings
Statistical Learning is a course designed for students who need to carry out statistical analysis, or “learning”, from real data. Emphasis will be placed on the development of statistical concepts and statistical computing. The content will be motivated by problem-solving in many diverse areas of application. This course will cover a range of topics in statistical learning including linear and non-linear regression, classification techniques, resampling methods (e.g., the bootstrap), regularisation methods, tree based methods and unsupervised learning techniques (e.g. principle components analysis and clustering).
Upon successful completion, students will have the knowledge and skills to:
- Use packages and process output relating to statistical learning in the statistical computing package R.
- Fit linear and non-linear regression models and analyse relationships between a response variable and covariates.
- Perform classification techniques on qualitative response variables.
- Assess models based on resampling methods.
- Carry out model selection based on regularisation methods.
- Utilise tree-based methods.
- Perform basic unsupervised learning techniques.
- Assignments (30) [LO 1,2,3,4,5,6,7]
- Exams (70) [LO 1,2,3,4,5,6,7]
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Students are expected to commit at least 10 hours per week to completing the work in this course. This will include at least 3 contact hours per week and up to 7 hours of private study time.
Requisite and Incompatibility
Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. (2013). An Introduction to Statistical Learning (with applications in R). Springer.
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
Offerings, Dates and Class Summary Links
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|2955||22 Feb 2021||01 Mar 2021||31 Mar 2021||28 May 2021||In Person||N/A|