- Code STAT4040
- 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, Finance, Statistics
This course provides an introduction to statistical learning and aims to develop skills in modern statistical data analysis. There has been a prevalence of “big data” in many different scientific fields. In order to tackle the analysis of data of such size and complexity, traditional statistical methods have been reconsidered and new methods have been developed for extracting information, or "learning", from such data. This course will cover a range of topics in statistical learning including linear regression, classification techniques, resampling methods (e.g., the bootstrap), regularisation methods, tree based methods, and unsupervised learning techniques (e.g., clustering). As the extensive use of statistical software is integral to modern data analysis, there will be a strong computing component in this course.
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Requisite and Incompatibility
You will need to contact the Rsch Sch of Finance, Actuarial Studies & App Stats to request a permission code to enrol in this course.
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
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
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|
|9577||18 Jul 2016||29 Jul 2016||31 Aug 2016||28 Oct 2016||In Person||N/A|