- Code STAT3017
- 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 research-led course provides an introduction to recent developments in Random Matrix Theory and Online Learning that addresses the challenges and opportunities posed by the availability of large amounts of data.
In the first instance, we will review some classic results from multivariate statistical theory, matrix analysis, and probability theory. Then we will present the salient statistical features of big data (e.g., heterogeneity, noise accumulation, spurious correlation, and incidental endogeneity) and show how this impacts on traditional statistical methods and theory.
We follow with an introduction to modern Random Matrix theory and its application in statistics. Applications presented may include topics such as high-dimensional statistical inference, large covariance matrices, large-scale statistical learning through subsampling, sparsification of large matrices, principal component analysis, and dimension reduction.
We conclude with an introduction to the theory of online learning (aka. sequential prediction) to handle the situation of streaming data.
The weekly 2-hour lectures will be accompanied by a 1-hour practical workshop where students will use and learn about the latest computational tools to work with big and streaming data sets. Example data sets may be drawn from areas such finance, web analytics, digital marketing, and satellite imagery data.
Indicative AssessmentTypical assessment may include, but is not restricted to: homework sets and a final exam.
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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
Assumed KnowledgeStudents are recommended to have completed or be enrolled in STAT3040
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 and Dates
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|8518||22 Jul 2019||29 Jul 2019||31 Aug 2019||25 Oct 2019||In Person||N/A|