APPLIED STATISTICS
STA3AS
2020
Credit points: 15
Subject outline
The purpose of STA3AS is to equip graduates with an in depth understanding of modern statistical methods in the following three key topics: 1. Sample surveys with an emphasis on simple random sampling and stratified random sampling. 2. Multivariate analysis with an emphasis on inference for the multivariate mean, checking for underlying multivariate normality, principal component analysis and discriminant analysis. This topic includes an introduction/review of common linear algebra results. 3. Time series analysis with an introduction into the theoretical foundation of Box-Jenkins univariate time series models which form a basis for empirical work with time series data. The software package used in this subject is R.
School: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: Paul Kabaila
Available to Study Abroad/Exchange Students: Yes
Subject year level: Year Level 3 - UG
Available as Elective: No
Learning Activities: N/A
Capstone subject: No
Subject particulars
Subject rules
Prerequisites: STM2PM OR STA2MD
Co-requisites: N/A
Incompatible subjects: STA4AS
Equivalent subjects: N/A
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Applied Multivariate Statistical Analysis
Resource Type: Book
Resource Requirement: Recommended
Author: Johnson, R.A. and Wichern, D.W.
Year: 2002
Edition/Volume: 5TH ED
Publisher: PEARSON
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Printed text available from University Bookshop
Resource Type: Book
Resource Requirement: Prescribed
Author: Paul Kabaila and Luke Prendergast
Year: N/A
Edition/Volume: N/A
Publisher: Department of Mathematics and Statistics
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Time Series Analysis: Forecasting and Control
Resource Type: Book
Resource Requirement: Recommended
Author: Box, G.E.P. and Jenkins, G.M.
Year: 1976
Edition/Volume: N/A
Publisher: REVISED ED., HOLDEN-DAY, 1976.
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Mathematical Statistics and Data Analysis
Resource Type: Book
Resource Requirement: Recommended
Author: Rice, J.A.
Year: 2007
Edition/Volume: 3RD EDN
Publisher: DUXBURY
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Melbourne (Bundoora), 2020, Semester 2, Day
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Paul Kabaila
Class requirements
LectureWeek: 31 - 43
Three 1.00 hour lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
PracticalWeek: 31 - 43
One 1.00 hour practical per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
3-hour short answer Final Examination | N/A | N/A | No | 70 | SILO1, SILO2, SILO3, SILO4 |
5 Assignments (approx. 240 words each) | N/A | N/A | No | 30 | SILO1, SILO2, SILO3, SILO4 |