SAQA

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SOUTH AFRICAN QUALIFICATIONS AUTHORITY

REGISTERED QUALIFICATION THAT HAS PASSED THE END DATE:

Doctor of Philosophy: Statistics

SAQA QUAL ID	QUALIFICATION TITLE
3589	Doctor of Philosophy: 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
Doctoral Degree	Field 10 - Physical, Mathematical, Computer and Life Sciences		Mathematical Sciences
ABET BAND	MINIMUM CREDITS	PRE-2009 NQF LEVEL	NQF LEVEL	QUAL CLASS
Undefined	360	Level 8 and above	NQF Level 10	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
73909	Doctor of Philosophy in Mathematical Statistics	Level 8 and above	NQF Level 10	360	Complete

PURPOSE AND RATIONALE OF THE QUALIFICATION

The qualification requires the demonstration at the highest level of the theoretical and/or practical skills of the learner in the formulation of new models and methods for the analysis and interpretation of data. The demonstration of problem-solving skills and the ability to formulate and solve questions in a mathematical or probabilistic framework is a major requirement. A learner who has attained this qualification can serve as a fully qualified statistician in Commerce or Industry and/or a teacher and researcher at a university or technikon.

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 and 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 without 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 hypothesis, generate facts and assemble data in pursuit of that hypothesis, evaluate these facts by means of appropriate Statistical analyses and to present them, in either 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 multi-disciplinary investigation and, if required, modify the proposal to accommodate any difficulties encountered.

Communicate results and findings in a clear, scientifically correct manner, either 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.

A Master's degree (or its equivalent) in Mathematical Statistics is required. It is required that the potential learner shall have attained a mark of at least 65% in the M.Sc. degree examinations.

Recognition of prior learning:

A learner who claims to have achieved entry requirements through experimental 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 and relate the findings to the existing body of knowledge in the field. Manage a team in a process as above.

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 either 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 multi-cultural 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 programme.
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 reasoning 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 an awareness and recognition of the need 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 an awareness of the need for continued study so as to remain constantly up to date.

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

10. Demonstrate an 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 of the learner is continuously monitored by the thesis supervisor via a weekly discussion of one to one and a half hour. The learner is required to conduct three public seminars on the research topic prior to completion of the thesis.

Summative assessment practices that will be implemented:

Integrated assessment, focusing on the achievement of the exit-level outcomes, will be done by means of a thesis, examined by two external examiners and by the supervisor. The learner is required also to submit, together with the thesis, a completed research paper in a form suitable for submission to a scientific journal. Acceptance of this paper by a journal is not, however, a prerequisite for attaining the qualification.

ARTICULATION OPTIONS

Access to qualifications on a lower level:

Potential learners who are in possession of a Master's degree in Statistics from an accredited university may apply to the department for acceptance to the study. There is no provision made for entry to the study programme in mid-stream.
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.
The department reserves the right to accept an applicant it deems suitable even if the applicant's previous experience or qualification is not obviously within the general concept of Statistics.

Access to qualifications on the same level:

Under normal circumstances there is no articulation between institutions during the course of study. However, learners who wish to switch to another qualification or subject at this institution, may do so. Credit for any research completed successfully will be granted, subject to its acceptance in the new qualification or subject.
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 work done at this university. Under normal circumstances this university will not give credit for research done at another tertiary institution.

Access to qualifications on a higher level:

Having obtained this qualification, the following possibilities for access to other qualifications do exist:

a postgraduate higher diploma at this or another institution

any other degree or programme at this or another institution.

MODERATION OPTIONS

External evaluation will be by the use of external assessors.

Normally two external examiners will be appointed to assess the thesis and they are drawn from other tertiary institutions or research institutions of appropriate standing. If a thesis warrants it, more examiners may be appointed.

CRITERIA FOR THE REGISTRATION OF ASSESSORS

Assessors should have at least a Doctoral degree 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 years' 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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