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The Graduate Certificate of Science (Applied Statistics) is designed for graduates in any discipline, especially the humanities, social sciences and health sciences, information systems or business and science graduates who have a professional interest in the use of statistics, plus those who have a need to use statistics in their work but have not had sufficient or current training in the area.
The postgraduate Applied Statistics program includes courses 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.
Note that these programs are available to international students, but only for international students who are studying in a country other than Australia. This is because students may only undertake a total of 4 units per year in these programs with a significant online component.
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
Graduates of the Graduate Certificate of Science (Applied Statistics) will be able to:
- Develop cognitive skills to review, analyse and consolidate statistical knowledge and identify and provide solutions to complex problems, and to think critically to generate complex statistical ideas
- Assemble specialised technical and creative statistical skills in diverse fields
- Synthesise communication skills to demonstrate an understanding of theoretical statistical concepts to transfer knowledge and ideas to a variety of audiences
- Defend the application of statistical knowledge and skills to make independent judgements in a range of technical or management functions in varied specialised contexts
- Initiate, plan, and implement a range of statistical analyses within varied specialised technical and/or creative contexts
- Demonstrate responsibility and accountability for personal outputs and all aspects of the work or function of others within broad parameters.
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
Applicants require either:
- Undergraduate degree and normally have an understanding of descriptive statistics
- Several years practical statistical experience in industry
English Language Requirements
Swinburne College English for Academic Purposes Certificate: EAP 5 Advanced: 70%; 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 of 79, with no individual band below 18.
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.
To qualify for a Graduate Certificate of Science (Applied Statistics), students must complete 4 units. Each unit carries 12.5 credit points.
Please note: You cannot re-enrol into Swinburne units 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
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 courses 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 course may be granted ‘credit’ and/or entry into the course 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
Eligible OUA students can access the government loan scheme known as FEE-HELP. You pay back the loan through your taxes once your income reaches a minimum threshold.
Who can access it?
- Australian citizens who will undertake, in Australia, at least one unit of study contributing to their course
- Permanent humanitarian visa holders who will be resident in Australia for the duration of their unit
- Permanent visa holders who are undertaking bridging study for overseas-trained professionals, and will be resident in Australia for the duration of their study
- Credit card (Visa and MasterCard)
- Money order
You should make cheques and money orders payable to 'Open Universities Australia' and send them to:
Open Universities Australia
GPO Box 5387
Please note: The Master of Science (Applied Statistics) has undergone a major change due to changes in the Australian Qualification Framework. Students who started their degree prior to 2015 can continue with the pre-2015 course. All students who began their studies from 2015 will need to study the new course structure.
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