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Graduate Diploma of Science (Applied Statistics) 

Z192     


Campus Availability Study Mode Study Level Duration
Hawthorn, Off-Campus Distance, Full-time, Part-time (day), Part-time (evening) Postgraduate One year full-time or two years part-time.

This program is designed for graduates in the humanities, social sciences and health sciences, who have a professional interest in the use of statistics. It is also applicable to other graduates who have a need to use statistics in their work but have not had sufficient or current training in the area. It concentrates on practical skills and enables participants to broaden their theoretical and practical knowledge of the basic areas of statistics.

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The graduate diploma aims to continue the statistical training provided by the graduate certificate, for people working with statistics in the social, life and health sciences or related areas. It aims to develop:
  • proficiency in a statistical software package such as SPSS
  • understanding of the need for and methods of acquiring good data. This is achieved through the inclusion of subject matter relating to data screening and survey design
  • well-rounded competent graduates with adequate quantitative skills in areas such as exploratory data analysis, estimation and hypothesis testing, measurement, modelling, risk analysis, forecasting and data mining
  • good communication, presentational and interpersonal (team-working) skills honed using assignment work and class discussion
  • a flexible approach to problem solving with an ability to listen and understand the advice and opinions of domain experts. These skills are developed through the use of actual problems and real data in lectures and assignments
  • proficiency in at least one of the following software packages in addition to SPSS (Access, EXCEL, SAS, STATA, MINITAB, WINASTSA)
  • experience in analysing multivariate data sets
  • learning the fundamentals of sampling and demographic techniques
  • data analysis skills in areas such as dimension reduction, model building in multiple regression, forecasting, experimental design and process control

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This program is part of a nested suite that includes the Graduate Certificate of Science (Applied Statistics), Graduate Diploma of Science (Applied Statistics) and the Master of Science (Applied Statistics)).
 
For the graduate diploma program, students will be required to complete eight units of study, at least three of these must be Level 2 units or higher. These include the four units of the graduate certificate. Students will be required to take one core unit in Level 2, HMS780, and the balance from electives. With approval, students may include units of study from Level 3 of the master program.
 
Each unit of study is worth 12.5 credit points. To complete the graduate diploma, students must gain a total of 100 credit points. Full-time students undertake four units of study per semester, part-time students undertake two units of study per semester. The class contact hours for each unit will normally be three hours per week for one semester, consisting of a combination of lectures and practical work as applicable to the topic.
 
Some units of study are available in off-campus flexible learning mode (distance education) or online mode. Off-campus units of study may be taken by students both within and outside Australia, but are not available to students enrolled as international students in Australia (ie. those with a student visa).
 
Applicants with suitable backgrounds may gain exemptions up to a maximum of 50% of the program, however, in most cases, a maximum of  two exemptions (25%) may be granted.
 
Note: International student visa holders are required to study full-time.

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The program comprises eight units of study:

Level 1

HMS770 Statistical Practice 1or equivalent
HMS771 Statistical Practice 2 or equivalent
HMS772 Basic Statistical Computing 
or
or

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Research assistant positions involving both the management and application of research in a wide variety of areas including government agencies, market research, education, medical and biological sciences, town planning and social research.

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 The graduate diploma program aims to produce students with the following attributes:
 
 Capable in their chosen professional, vocational or study areas:
  • an in-depth understanding of the techniques used in practical statistical applications in the workplace
  • ability to apply knowledge to basic statistical questions
Operate effectively in work and community situations:
  • ability to communicate effectively with clients from a wide variety of backgrounds who need to make use of statistical analysis
  • ability to work effectively as individuals and in teams
  • statistical professionals need good communication skills, requiring an understanding of client’s needs and the ability to interpret the results in terms understandable by them
 Adaptable and able to manage change:
  • understanding of the changing and developing methods in the area of statistical analysis
  • ability to identify, formulate and solve problems
  • expectation of the need to undertake life-long learning, and the capacity to do so
  • independent learning ability and self-motivation are important attributes for professional statisticians
Aware of environments in which they will be contributing:
  • understanding the role of statistical analysis for revealing underlying relationships and behaviours in business and society.
  • statistical educators have a professional responsibility to maintain skill levels and keep up-to-date with advances in statistical techniques in order to best prepare students for the workplace.
Entrepreneurial in contributing to innovation and development within their business, workplace or community:
  • ability to critically understand and contribute to innovations and developments in statistics practice
  • by focusing on the use of statistical analysis in a wide range of disciplines, students are exposed to a broad variety of applications in areas such as market research, business, sports and health industries

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A degree from a recognised tertiary institution or approved equivalent. It is also desirable that applicants have work experience in a related area.

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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.

Further details for students considering Higher Education courses: http://www.swin.edu.au/corporate/registrar/ppd/files/stuinf.htm

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In 2009, tuition fees for this program are based on $1650 per 12.5 credit point unit of study. In the event that a unit of study is derived from another program, the applicable fee will be that of the other program.  All fees are reviewed each year and may increase without notice.

HELP
The Higher Education Loan Program (HELP) is a suite of income-contingent loans for Australian citizens and holders of Australian permanent humanitarian visas. FEE-HELP (previously PELS) is available to eligible fee-paying undergraduate and postgraduate students. It provides students with a loan to cover their tuition fees (lifetime maximum $83,313 from 1 January 2009). The FEE-HELP limit is indexed on 1 January each year.

Note: New Zealand citizens and holders of other Australian permanent resident visas do not have access to HELP loans. These students must pay their student contributions or tuition fees up front without a discount.

For further information on your support and study options visit the 'Going to Uni' website at: http://www.goingtouni.gov.au

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Applications for mid-year entry will be accepted until Friday 17 July 2009. Applications submission details can be found on the application form and can be downloaded from the website at: www.swinburne.edu.au/hed/postgrad/apply  

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Postgrad City Session
Question Everything in the one spot
Wednesday 1 July 2009
6.00pm - 8.30pm
Melbourne CBD
 
Attend the Swinburne Postgraduate Q&A night in the city to find out more about Mid-year entry for postgrad programs. Register online now www.swinburne.edu.au/citysession

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Web: Enquire online

Tel: 1300 ASK SWIN (1300 275 794)
 

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