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Graduates of the Graduate Diploma of Applied Statistics will be able to:
- Demonstrate advanced abilities to critically think, review, analyse and consolidate statistical knowledge to provide solutions to complex problems in diverse fields
- Synthesis communication skills to demonstrate an understanding of theoretical statistical concepts to transfer complex knowledge and ideas to a variety of audiences
- Defend the application of advanced statistical knowledge and skills to make high level, independent judgements in a range of technical or management functions in varied advanced contexts
- Demonstrate responsibility and accountability for personal outputs and all aspects of the work or function of others within broad parameters
- Demonstrate ability to perform advanced statistical modelling techniques using a variety of software.
The demand for applied statisticians continues to grow as data production grows in all areas of the economy. Graduates are employed in areas such as the following:
- Government agencies
- Market research
- Medical and biological sciences
- Town planning
- Social research
- Medical Research
The postgraduate Applied Statistics program aims to enable students to develop:
- Proficiency in statistical software packages such as SPSS and SAS
- An understanding of the need for, and methods of, acquiring good data
- Quantitative skills in areas such as exploratory data analysis, estimation and hypothesis testing, factor and regression analysis, discriminant analysis and forecasting
- An appreciation for the role of statistical analysis for revealing underlying relationships and behaviours in business and society
Applicants require either:
- Undergraduate degree and normally have an understanding of descriptive statistics; or
- Have successfully completed the Graduate Certificate of Applied Statistics
English Proficiency Requirements
English Language Requirements: (International students only)
Swinburne College English for Academic Purposes Certificate: Swinburne English Language Centre: EAP 5 Advanced level with overall 70% and all skills 65% or above; OR, obtaining a minimum IELTS overall band of 6.5 (Academic Module) with no individual band below 6.0; OR, a TOEFL (Paper-based) minimum score of 550 (with Test of Written English (TWE) score of 5); OR, a TOEFL (Internet-based) minimum score 79 (Reading no less than 18, Writing no less than 20).
The media used to teach this course include printed materials and also some online study material. You will need easy and frequent access to a computer with the internet and email.
Additionally, students will be required to purchase and/or have access to the statistical software package SPSS.
SAS software required in Graduate Diploma and Master of Science units will be supplied by DVD. Please note: SAS will only run on a Windows platform.
Recognition of Prior Learning (RPL)
Recognition of Prior Learning (RPL) is a process where a student may be granted credit or partial credit towards a qualification in recognition of skills and knowledge gained through work experience, life experience and/or formal training. For further details for students considering Higher Education degrees visit the RPL website: http://www.future.swinburne.edu.au/pathways/workforce/index.html
Applicants with prior tertiary studies that satisfy part of the academic requirements of this degree may be granted ‘credit’ and/or entry into the degree with ‘advanced standing’. University policies apply and applicants are assessed on a case-by-case basis. For further information please refer to http://www.swinburne.edu.au/open-universities-australia/advanced-standing-rpl.html
The Graduate Diploma of Applied Statistics is designed for graduates in any discipline, especially for humanities, social sciences, health sciences, information systems, business and science graduates who have a professional interest in the use of statistics. It is also applicable to other graduates who have a need to use advanced statistics in their work,but have not had sufficient or current training in applied statistics. It concentrates on practical skills, but also broadens and builds theoretical knowledge of key areas of statistics.
The postgraduate Applied Statistics program includes degrees from the Graduate Certificate, Graduate Diploma and Master levels. In particular it builds proficiency in the SAS software package as well as SPSS. It provides students with experience in analysing multivariate data sets and in the analysis of complex sample data.
To qualify for a Graduate Diploma of Applied Statistics, students must complete 8 subjects (100 credit points). Subjects normally carry 12.5 credit points.
Please note: You cannot re-enrol into Swinburne subjects that you have already passed.
Absent Without Leave and Leave of Absence: How to apply for an approved leave of absence and minimise the risk of having to reapply for degree admission: http://www.swinburne.edu.au/open-universities-australia/current/AWOL-and-LOA.html
From Study Period 1 2018, the Master of Science (Applied Statistics) will change to the Master of Applied Statistics. This is a Course Title change only: the Course Structure remains the same with some minor changes to unit titles.
Master of Applied Statistics and nested courses including the Graduate Certificate and Graduate Diploma
Students may choose to stay in the old Course or transfer to the new Course. Students who wish to transfer to the new Course title must complete the online Course Transition Application to change your Course before the close of enrolments for SP1, 2018 - 26 January 2018.
Master of Science (Applied Statistics) and nested courses including the Graduate Certificate and Graduate Diploma
If you are enrolled in one of the nested levels of the Course (Graduate Certificate or Graduate Diploma) and are interested to apply for and enrol in the masters, you must submit an OUA Course Transition Application online before close of enrolments for SP4, 2017 – 27 October 2017. This is the last date that enrolments will be accepted.
For all students: Minor changes to unit titles:
- STA60003 Basic Statistical Computing changing to STA60003 Basic Statistical Computing using R
- STA80005 Statistical Marketing Tools changing to STA80005 Advanced Data Mining
- STA80006 Using R for Statistical Analysis changing to STA80006 Statistical Decision Making