SAQA

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SOUTH AFRICAN QUALIFICATIONS AUTHORITY

REGISTERED QUALIFICATION THAT HAS PASSED THE END DATE:

Master of Science: Statistics

SAQA QUAL ID	QUALIFICATION TITLE
3593	Master of Science: Statistics
ORIGINATOR
Rand Afrikaans University
PRIMARY OR DELEGATED QUALITY ASSURANCE FUNCTIONARY			NQF SUB-FRAMEWORK
Was CHE until Last Date for Achievement			HEQSF - Higher Education Qualifications Sub-framework
QUALIFICATION TYPE	FIELD		SUBFIELD
Master's Degree	Field 10 - Physical, Mathematical, Computer and Life Sciences		Mathematical Sciences
ABET BAND	MINIMUM CREDITS	PRE-2009 NQF LEVEL	NQF LEVEL	QUAL CLASS
Undefined	240	Level 8 and above	NQF Level 09	Regular-Provider-ELOAC
REGISTRATION STATUS		SAQA DECISION NUMBER	REGISTRATION START DATE	REGISTRATION END DATE
Passed the End Date - Status was "Reregistered"		SAQA 2663/05	2006-07-01	2009-06-30
LAST DATE FOR ENROLMENT		LAST DATE FOR ACHIEVEMENT
2010-06-30		2013-06-30

In all of the tables in this document, both the pre-2009 NQF Level and the NQF Level is shown. In the text (purpose statements, qualification rules, etc), any references to NQF Levels are to the pre-2009 levels unless specifically stated otherwise.

This qualification is replaced by:

Qual ID	Qualification Title	Pre-2009 NQF Level	NQF Level	Min Credits	Replacement Status
74036	Master of Science: Statistics	Level 8 and above	NQF Level 09	240	Complete

PURPOSE AND RATIONALE OF THE QUALIFICATION

The primary purpose of this qualification is to provide qualifying learners with the ability to:

Develop theoretical and/or practical skills in the formulation of new models and methods for the analysis and interpretation of data, and to a much higher level than in the Honours degree.

Develop problem-solving skills and the ability to formulate, and solve, questions in a mathematical or probabilistic framework.

The qualification prepares learners for, and provides a basis for:

A career as Statistician in Commerce or Industry

An academic career at a University or Technikon

Entrance to a Ph.D. qualification.

LEARNING ASSUMED TO BE IN PLACE AND RECOGNITION OF PRIOR LEARNING

Learners accessing this qualification should demonstrate their ability to:

Identify problems within the discipline of Statistics or any field of its application and plan suitable projects to address the identified problem

Generate experimental data in projects at high levels of complexity commensurate with the level of the qualification, make correct interpretations and appropriate deductions

Operate easily in the philosophy of the science of Statistics and related fields

Work in groups with others in the solution of problems and carrying out of projects

Work effectively under supervision in the performance of research projects and the compilation of reports

Find, evaluate and integrate appropriate literature and be able to generate, analyse and evaluate experimental data at high level

Use technical language and terminology with a high level of competence in the processing and presentation of reports in either written or oral form

Integrate factual information into a cohesive whole, relate it to other areas and disciplines and develop new concepts there from

Participate responsibly in activities which impinge on, and lead to improvement, of societal quality of life by demonstration and avoidance of practices which will negatively affect the well-being of others

Investigate employment possibilities

Investigate and evaluate entrepreneurial possibilities in the field of Statistics and related competence

Find information by the correct usage of information retrieval systems, to collate and interpret such information and place it in context with known information

Generate information by correct and appropriate use of technology and research methodology

Plan and execute a research programme at the appropriate level of expertise

Formulate hypotheses, generate facts and assemble data in pursuit of that hypothesis, evaluate these facts by means of appropriate Statistical analyses and present them, in verbal or written form, with due regard to clarity, correctness of technical terminology and language usage

Function in collaboration with workers in other disciplines with due regard to correctness of technique used and interpretation of results

Work harmoniously with co-workers in the same working environment

Identify a research area, plan a detailed and multidisciplinary investigation and, if required, modify the proposal to accommodate any difficulties encountered

Communicate results and findings in a clear, scientifically correct, manner, verbally or in the form of written submissions

Work without being driven

Function in the philosophy of the Statistics discipline and associated disciplines by the generation of new insights and interpretations

Maintain the highest levels of probity and professionalism as shown by accuracy of results and honesty in evaluation, interpretation and presentation.

An Honours degree (or its equivalent) in Mathematical Statistics, or an Honours degree in Mathematics, Applied Mathematics or Computer Science which included a strong Statistical component.

It is required that the potential learner shall have attained a mark of at least 65% in the Honours degree examinations.

Recognition of prior learning:

A learner who claims to have achieved entry requirements through experiential learning will be assessed. If the student is found to be competent the student may gain:

access,

advanced placement

or recognition of degree status will be granted on condition of continuing education.

RECOGNISE PREVIOUS LEARNING?

EXIT LEVEL OUTCOMES

The learners should be able to:

1. Identify a problem, formulate an appropriate hypothesis, generate experimental data, make correct interpretations and appropriate deductions.

2. Work harmoniously in a managerial capacity with co-workers in the same working environment, in groups with others in the solution of problems and the carrying out of projects.

3. Work independently in the mastery of subject contents, the performance of practical projects and the compilation of reports.

4. Plan and execute a research programme under supervision and relate the findings to the existing body of knowledge in the field.

5. Find, evaluate and integrate technical literature, use appropriate and correct technical language and terminology in reports.

6. Perform the practice of science and technology effectively and responsibly.
Develop new scientific procedures to analyse non-standard problems.

7. Plan, analyse and honestly reporting on an investigation with due regard to the impact of the problem and its solution on the physical or social environment and, if required, modify the proposal to accommodate any problems or difficulties encountered.

8. Use different techniques to assimilate and analyse data, by reading, discussion, calculation, reporting and presentation of projects and seminars.

9. Be able to explain the relevance and importance of the specific subject to the community.

10. Demonstrate awareness of the impact of statistical science on a multicultural societal environment and the differing needs and expectations of society.

11. Investigate further possibilities of training and employment.

ASSOCIATED ASSESSMENT CRITERIA

The learner can:

1. Display a thorough knowledge of the field of enquiry.
Formulate an appropriate hypothesis.
Plan and carry out an appropriate experimental program.
Analyse results obtained correctly.

2. Co-operate with fellow workers.
Contribute meaningfully to group efforts to work on a problem.
Manage teamwork.

3. Display a mastery of subject material by independent study.
Work on a project of high complexity successfully.
Write a project or progress report of high standard independently.

4. Present a suitable project proposal on a topic.
Be able to motivate the reason behind the proposal satisfactorily.
Be able to perform the actions required to complete the collection of information.
Be able to relate the information obtained to that which is known.

5. Display knowledge of current information retrieval systems and processes.
Demonstrate a mastery of the use of technical and professional language and terminology.

6. Demonstrate awareness and recognition of the needs for careful and correct statistical techniques.
Use appropriate technology correctly, safely and responsibly.
Analyse non-standard problems.

7. Present a project proposal in which all the appropriate aspects relating to the broad social and environmental considerations are addressed.
Be able to suggest possible changes in the proposal should certain aspects not turn out as expected.

8. Show awareness of the need for different ways of learning and assimilation of knowledge by electronic calculation and retrieval systems, libraries, correspondence and personal contacts at meetings.
Show awareness of the need for continued study so as to remain constantly up to date.

9. Demonstrate awareness of he importance of making valid conclusions from experimental data.

10. Demonstrate awareness of where the chosen field of study impinges on society and where further studies may be done. This includes medicinal, industrial, recreational and aesthetic considerations.

11. Demonstrate the ability to relate the field of study to society and thus know where those skills are likely to be required.

Formative assessment practices that will be implemented:
The progress for the dissertation is continuously monitored by a supervisor via a weekly discussion. The progress for the coursework (four modules and dissertation) is also continuously monitored by a supervisor via a weekly discussion. The problem-solving skills of learners are continuously assessed via homework assignments in the coursework modules.

Summative assessment practices that will be implemented:
Integrated assessment, focusing on the achievement of the exit-level outcomes, will be done by means of written examinations in the modules and a dissertation, examined by two external examiners and by the supervisor. The external examiners are recognised authorities on the topic addressed in the dissertation. The dissertation must address an as yet unsolved problem in Statistics. The context of the problem must be clarified and its possible connections with other statistical theories and/or methodologies described. The learner is required to put forward, and evaluate, a proposal towards resolution of the problem. The evaluation of the proposal may take the form of a numerical study or of a theoretical analysis.

ARTICULATION OPTIONS

Access to qualifications on a lower level:
Learners who have been, or are, registered for this or similar qualification at another institution of higher education, may be allowed under very exceptional circumstances, to enter in mid-stream. Any application for such entry will be evaluated ad hoc by the department, subject to approval by the Dean's committee of the Faculty of Science. Credit may be retained for any subjects so approved.
Learners who apply on the basis of non-formal prior learning will be evaluated according to the procedures formulated by the university for such purpose.

Access to qualifications on the same level:
Learners who wish to switch to another qualification or subject at this institution may do so within the prescribed period for such changes.
Learners who wish to continue their studies at another institution, may do so. The institution to which the relocation is made will decide on acceptance of credit for all modules passed at this university.

Access to qualifications on a higher level:
Having obtained this qualification, the following possibilities for access to other qualifications do exist:
*A post graduate higher diploma at this or another institution
*A Ph.D. degree or similar programme at this or another institution
*A Master's degree or similar programme at this or another institution.

MODERATION OPTIONS

External evaluation will be the inclusion of external assessors.

One external examiner will be appointed for each module and they are likely to be drawn from other tertiary institutions or research institutions of appropriate standing.

CRITERIA FOR THE REGISTRATION OF ASSESSORS

Assessors should have at least a level 8 qualification in the appropriate discipline.

Assessors should have at least five years' experience in the appropriate discipline, at tertiary institution level or a level of equivalent status outside the tertiary establishment.

Assessors should have had at least five year's exposure to assessment practices at tertiary or equivalent level.

REREGISTRATION HISTORY

As per the SAQA Board decision/s at that time, this qualification was Reregistered in 2006.

LEARNING PROGRAMMES RECORDED AGAINST THIS QUALIFICATION:

When qualifications are replaced, some of their learning programmes are moved to being recorded against the replacement qualifications. If a learning programme appears to be missing from here, please check the replacement.

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PROVIDERS CURRENTLY ACCREDITED TO OFFER THIS QUALIFICATION:

This information shows the current accreditations (i.e. those not past their accreditation end dates), and is the most complete record available to SAQA as of today. Some Primary or Delegated Quality Assurance Functionaries have a lag in their recording systems for provider accreditation, in turn leading to a lag in notifying SAQA of all the providers that they have accredited to offer qualifications and unit standards, as well as any extensions to accreditation end dates. The relevant Primary or Delegated Quality Assurance Functionary should be notified if a record appears to be missing from here.

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