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SOUTH AFRICAN QUALIFICATIONS AUTHORITY 
REGISTERED QUALIFICATION: 

Doctor of Philosophy in Biostatistics 
SAQA QUAL ID QUALIFICATION TITLE
119583  Doctor of Philosophy in Biostatistics 
ORIGINATOR
Stellenbosch University 
PRIMARY OR DELEGATED QUALITY ASSURANCE FUNCTIONARY NQF SUB-FRAMEWORK
-   HEQSF - Higher Education Qualifications Sub-framework 
QUALIFICATION TYPE FIELD SUBFIELD
Doctoral Degree  Field 10 - Physical, Mathematical, Computer and Life Sciences  Physical Sciences 
ABET BAND MINIMUM CREDITS PRE-2009 NQF LEVEL NQF LEVEL QUAL CLASS
Undefined  360  Not Applicable  NQF Level 10  Regular-Provider-ELOAC 
REGISTRATION STATUS SAQA DECISION NUMBER REGISTRATION START DATE REGISTRATION END DATE
Reregistered  EXCO 0333/25  2025-07-10  2028-07-10 
LAST DATE FOR ENROLMENT LAST DATE FOR ACHIEVEMENT
2029-07-10   2032-07-10  

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 does not replace any other qualification and is not replaced by any other qualification. 

PURPOSE AND RATIONALE OF THE QUALIFICATION 
Purpose:
The purpose of the Doctor of Philosophy in Biostatistics is to mentor candidates in the theory and methodology of biostatistics and develop internationally comparable biostatisticians with technical skills, scholarly integrity, and professional ethics to address public health problems, ensure advancement in the field of biostatistics and collaborate with peers from diverse academic backgrounds without compromising independent critical thinking. This qualification is composed of a thesis containing an original contribution on a topic in Biostatistics.

The qualifying learners will possess expertise and advanced knowledge at the cutting edge of biostatistics achieved through independent study and will be able to propose new research questions and answer them by research and use the results to generate new knowledge.

Upon completion of the qualification, qualifying learners will be able to:
  • Participate in academic discussions regarding biostatistics, research methods and approaches to generate new knowledge.
  • Develop new methods and approaches to generate and use knowledge in biostatistics to address questions and solve problems in the field.
  • Identify shortcomings in data/methodologies and address such shortcomings in an iterative process.
  • Undertake independent research, with minimal supervision, at the most advanced academic levels culminating in the submission, assessment, and acceptance of a thesis.
  • Demonstrate the ability to evaluate the research at the forefront of biostatistics based on knowledge of the relevant literature and applicable research methodologies.
  • Demonstrate a high level of independent research capability and make a significant and original contribution to knowledge at the frontiers of biostatistics.
  • Recognize gaps in current biostatistical methods and propose efficient methods based on rigorous theoretical justification.
  • Work independently and take ownership and responsibility for the management of the project.
  • Apply and undertake research independently at an internationally comparable level and communicate the results of original and innovative research at a similar level by both peer-reviewed publications as well as by seminar and conference presentations and communicate the science effectively to both specialists and lay audiences.
  • The graduate will be intellectually independent and will be able to manage his or her research independently. He or she will be able to communicate biostatistical concepts effectively and effectively collaborate with research scientists in related
    disciplines.
  • Consider ethical issues in scientific research and the application of outcomes to the broader society.

    Rationale:
    There is a shortage of highly skilled Biostatisticians in South Africa and Sub-Saharan Africa resulting in an overreliance on input from biostatisticians sourced from economically developed countries for writing competitive grants, executing statistical procedures, and conducting advanced data analysis, publishing in high profile journals and teaching biostatistics at the postgraduate level. Several publications have highlighted the shortage of highly skilled biostatisticians in South Africa and Sub-Saharan Africa. The qualification focuses on the advancement of biostatistical methodology that can be utilized in biomedical sciences and public health and prepare candidates for a leadership role.

    The demand for trained biostatisticians continues to increase as the world becomes more dependent on predictive data and numerical reasoning, particularly related to research in the health sciences. Biostatistics applies statistical and probability theory to human health and disease. The qualification prepares learners to develop or adapt statistical methods for solving problems in the health field. The qualification is interdisciplinary in nature and learners will collaborate with researchers as they need to use real data to demonstrate the biostatistical methods they will be working on.

    The qualification meets specific needs in Biostatistics because the qualification aims to educate learners to be independent researchers and Biostatistics professionals in academia, research institutes such as the South African Centre of Excellence in Modelling and Analysis (SACEMA), South African Field Epidemiology/Biostatistician Training Program (SAFETP), National Institute for Communicable Disease (NICD), government or industry and Medical Research Council. While learners sometimes seek additional training after graduation through postdoctoral fellowships, a learner of the qualification is prepared to be a faculty member of a learner program in a university or a position in a public health organisation, multidisciplinary setting, government, or industry. 
    		•

    LEARNING ASSUMED TO BE IN PLACE AND RECOGNITION OF PRIOR LEARNING 
    Recognition of Prior Learning (RPL):
    The institution has an approved Recognition of Prior Learning (RPL) policy which is applicable to equivalent qualifications for admission into the qualification. RPL will be applied to accommodate applicants who qualify. RPL thus provides alternative access and admission to qualifications, as well as advancement within qualifications. RPL may be applied for access towards the qualification.

    RPL for access:
  • Learners who do not meet the minimum entrance requirements or the required qualification that is at the same NQF level as the qualification required for admission may be considered for admission through RPL.
  • To be considered for admission in the qualification based on RPL, applicants should provide evidence in the form of a portfolio that demonstrates that they have acquired the relevant knowledge, skills, and competencies through formal, non-formal and/or informal learning to cope with the qualification expectations should they be allowed entrance into the qualification.

    Entry Requirements:
    The minimum entry requirement for this qualification is:
  • Master of Science in Biostatistics, NQF Level 9.
    Or
  • Master of Science in Mathematics, NQF Level 9.
    Or
  • Master of Science in Applied Statistics, NQF Level 9. 
    		•

    RECOGNISE PREVIOUS LEARNING? 
    Y 

    QUALIFICATION RULES 
    This qualification consists of the following compulsory module at National Qualifications Framework Level 10 totalling 360 Credits.

    Compulsory Module, Level 10, 360 Credits:
  • Thesis, 360 Credits. 
    		•

    EXIT LEVEL OUTCOMES 
    1. Undertake independent research, with minimal supervision, at the most advanced academic levels culminating in the submission, assessment, and acceptance of a thesis.
    2. Demonstrate the ability to evaluate the research at the forefront of biostatistics based on knowledge of the relevant literature and applicable research methodologies.
    3. Demonstrate a high level of independent research capability and make a significant and original contribution to knowledge at the frontiers of biostatistics.
    4. Recognize gaps in current biostatistical methods and propose efficient methods based on rigorous theoretical justification.
    5. Contribute to scholarly debates around theories of knowledge and processes of knowledge production in an area of study or practice.
    6. Effectively collaborate with research scientists in related disciplines and communicate biostatistical concepts effectively.
    7. Apply specialist knowledge and theory in critically reflexive, creative, and novel ways to address complex practical and theoretical problems.
    8. Engage in interdisciplinary activities in collaboration with communities, organizations, and other stakeholders in research, practice, and policy. 

    ASSOCIATED ASSESSMENT CRITERIA 
    Associated Assessment Criteria for Exit Level Outcome 1:
  • Examine and apply the steps required for descriptive, explanatory, and evaluative research.
  • Prepare a comprehensive research proposal including, inter alia, a reasoned argument to justify the proposed research, a systematic reasoned theoretical argument with a theoretical model as the result, a substantive research hypothesis and a description and evaluation of the research design.
  • Plan and conduct research, using appropriate research methods such as instrument design, protocol, operating procedures, and project management for the solving of problems in health science.
  • Write up a thesis based on research.
  • Present research findings and defend thesis during an oral examination.

    Associated Assessment Criteria for Exit Level Outcome 2:
  • Rigorously critique and evaluate current research in quantitative health sciences and participate in scholarly debates in the field of biostatistics.
  • Conduct a comprehensive literature review regarding current research in biostatistics under supervision.

    Associated Assessment Criteria for Exit Level Outcome 3:
  • Identify, conceptualise, design, and implement research in medical, pharmaceutical, and public health fields.
  • Critically evaluate and utilise a wide range of basic and complex statistical tools for solving research problems.

    Associated Assessment Criteria for Exit Level Outcome 4:
  • Evaluate and apply the steps required for descriptive, explanatory, and evaluative research.
  • Critique the advanced-level biostatistical methods including descriptive and graphical analyses, null hypothesis testing and p-values, generalised linear models including linear, logistic, Poisson, survival, and time to event models (Cox and parametric survival), and generalised estimating equations.
  • Design, select and apply advanced biostatistical methods including linear mixed models, frailty models, weighted regression, multiple imputations/missing data handling methods processes or technologies to complex practical and theoretical problems.

    Associated Assessment Criteria for Exit Level Outcome 5:
  • Conduct independent and original research to further knowledge in the field of specialization and utilization of that knowledge for solving real life problems.

    Associated Assessment Criteria for Exit Level Outcome 6:
  • Present and effectively communicate the results of quantitative health sciences research to specialist and non-specialist audiences using the resources of an academic/professional discourse.
  • Defend the thesis through oral presentation after submission and examination.
  • Publish the research findings in a peer-reviewed scientific journal.
  • Expand, redefine, and reconfigure existing knowledge within the broader context of the field or inter/multi-disciplinary fields.

    Associated Assessment Criteria for Exit Level Outcome 7:
  • Make an original and significant contribution to knowledge in their area of research.
  • Engage in highly advanced critical thinking and creative problem solving within a focussed research context.

    Associated Assessment Criteria for Exit Level Outcome 8:
  • Consult biomedical researchers and provide advice on study design and statistical analysis plans.
  • Provide leadership in biostatistics research studies.
  • Work with others as part of a team, group, organization, or community to contribute to scholarly debates.
  • Apply efficient oral, verbal, and written communication using visual, mathematical and /or language skills with the aim of persuading.

    INTEGRATED ASSESSMENT
    Integrated Assessment in the qualification provides an opportunity for learners to show that they can integrate concepts, ideas, and actions across this qualification to achieve competence that is grounded and coherent with the purpose of this qualification. Integrated assessment will show how already demonstrated competence in individual areas can be linked and applied for the achievement of a holistic outcome as described in the Exit Level Outcomes.

    Integrated Assessment will judge the quality of the observable performance, and the quality of the reasoning that lies behind it. Assessments tools will encourage learners to give an account of the thinking and decision-making that underpin their demonstrated performance. Integrated assessment in this qualification allows the learners to demonstrate applied competence and uses a range of formative and summative assessment methods.

    Formative assessment:
    Formative assessment includes regular meetings with the supervisor/s, the annual progress seminar to an audience of peers, possible additional course work and feedback from peer reviewers on articles.

    Summative assessment:
    The degree is assessed by examination of a submitted thesis, i.e., summative assessment. The thesis format will align with that of the Faculty of Medicine and Health Sciences. The examination of the thesis is performed by one unattached, internal (academic associated with the institution, but not the supervisor) and two external examiners, not associated with the institution, and with whom there has been no collaborative project undertaken in the five-year period preceding the examination. One of the external examiners should preferably be from an international institute or university.

    The internal and external examiners will read the thesis and prepare a report. The report will be a critical assessment of the thesis in terms of the criteria prescribed by the Faculty of Medicine and Health Sciences and will typically include an assessment of the scientific merit of the work as specified by the rules of the faculty. The examiners will indicate whether the thesis should be accepted as is, accepted with minor or major (typically additional research) modifications, or rejected. The examiners will submit their reports to the Faculty Doctoral office.

    The Head of the Doctoral Office will forward all examiners' reports to the Post-graduate Committee of the Division of Epidemiology and Biostatistics, who will consider the recommendations of the examiners, and communicate it to the supervisor. It is the responsibility of the supervisor to ensure that all modifications to the thesis are made as requested by the examiners.

    If there is a significant difference in the assessment by the three examiners (for instance accept, accept, and reject), the Post-graduate Committee can request the assessment of a fourth examiner. The Faculty Board will then decide on the outcome of the examination process after considering the report of the fourth examiner.

    An oral will be set up by the Division where the candidate, examiners, and supervisors (as observers) will join. The candidate will also be expected to answer questions related to the thesis to the satisfaction of the examiners. 
    		•

    INTERNATIONAL COMPARABILITY 
    The qualification is comparable with similar qualifications offered by the following countries.

    Country: United States of America.
    Institution: The George Washington University.
    Qualification: Doctor of Philosophy in Biostatistics.
    Duration: Three years full time
    Credits: 72

    Entry Requirements:
    The George Washington University (GWU) qualification requires a master's degree in statistics, biostatistics, mathematics, or applied mathematics from a regionally accredited institution.

    Purpose/Rationale:
    The Biostatistics qualifications were created to help meet the ever-increasing demand for biostatisticians to take leadership roles in careers as researchers and educators in academia, government, and industry. The Ph.D. program produces biostatisticians who can develop a biostatistical methodology that can be used to solve problems in public health and the biomedical sciences. In addition, graduates are prepared to apply biostatistical and epidemiology methodology for the design and analysis of public health and biomedical research investigations. Finally, graduates are well suited to function as collaborators or team leaders on research projects in the biomedical and public health sciences.

    On completion of the GWU qualification, qualifying learners will be able to:
  • Develop careers in academia, research institutes, government, and industry.
  • Evaluate and apply a range of current statistical methods and practices in the health sciences.
  • Apply solid theoretical knowledge necessary for the development and study of new statistical methods.
  • Assume all responsibilities of a statistician in collaborative health science research; in particular, the graduate will have experience in the design, data management, analysis, and interpretation of a variety of experimental and observational studies.
  • Develop experience in writing reports and giving oral presentations describing health science studies.

    Qualification structure:
    The following requirements must be fulfilled: 72 credits, including a minimum of 52 credits in required and elective courses and a minimum of 6 credits in thesis research; successful completion of the general and final examinations; and completion of the professional enhancement requirement.

    Compulsory Modules.
  • Statistics, 30 credits.
  • Public health, 11 credits.

    Elective Modules, 9 credits:
    Approved statistics electives (at least 3 credits must be selected from the following):
  • Applied Linear Models .
  • Categorical Data Analysis.
  • Nonparametric Inference.

    6 credits in electives from the following approved lists of Statistics and Public Health Modules:
  • Methods of Statistical Computing I.
  • Methods of Statistical Computing II.
  • Applied Multivariate Analysis I.
  • Applied Multivariate Analysis II.
  • Design of Experiments.
  • Bayesian Statistics: Theory and Applications.
  • Modern Regression Analysis.
  • Sample Surveys.
  • Topics in Statistics.
  • Probability.
  • Distribution Theory.
  • Advanced Statistical Theory I.
  • Advanced Statistical Theory II.
  • Multivariate Analysis.
  • Stochastic Processes I.
  • Stochastic Processes II.
  • Advanced Time Series Analysis.
  • Topics in Sample Surveys.
  • Advanced Reading and Research.

    Approved public health electives:
  • Clinical Epidemiology and Public Health: Reading the Research.
  • Cancer Epidemiology.
  • Infectious Disease Epidemiology.
  • Measurement in Public Health and Health Services.
  • Consulting, 2 credits.
  • Doctoral Biostatistics Consulting Practicum.
  • Principles of Biostatistical Consulting.
  • Thesis research, 6 to 24 credits.
  • Thesis Research.

    Assessment:
    The general examination is given in two parts:
    Formative assessment:
    The qualifying exam is a written comprehensive examination based on the course content of Statistics and Public Health. The qualifying examination is given over a two-day period in the beginning of the fall semester of every academic year and consists of one four-hour theory exam and one two-hour biostatistical methods/applications exam. Learners are expected to take the comprehensive examination within 24 months from the date of enrolment in the program. A learner who fails to pass the comprehensive examination may, with the approval of the faculty, repeat the examination the following year. Failure on the second attempt results in termination from the PhD program. All examination questions focus on material that a person seeking a PhD in biostatistics is expected to know, regardless of subsequent specialization. The examination encompasses material in core mathematical statistics, and biostatistical methods courses in the PhD program in biostatistics.

    Summative assessment:
    The research proposal consists of an oral examination based on a written thesis research proposal. As soon as feasible after successful completion of the comprehensive exam, learners are encouraged to identify a thesis advisor and a topic of research. The written thesis proposal is then submitted to the student's Thesis Research Committee, and the learner makes an oral presentation of their proposal to the Committee. The Committee determines the learner's readiness to pursue and successfully complete the proposed research, in addition to the appropriateness of the specific problem for thesis-level research.

    Upon successful completion of the required coursework and both parts of the general examination, the candidate is generally recommended to the Associate Dean for Graduate Affairs of the Columbian College of Arts and Sciences (CCAS) for promotion to PhD candidacy- the thesis research. A candidate must file an approved thesis research plan with CCAS before being admitted to PhD candidacy. Prior to completion of the general examination, a learner may register for at most 6 credits of BIOS 8999.

    Similarities:
  • The George Washington University (GWU) and the South African (SA) qualifications require a master's degree in statistics, biostatistics, mathematics, or applied mathematics from a regionally accredited institution.
  • Both the GWU and SA qualifications are offered over a period of three years full time study.
  • Both qualifications are assessed through formative and summative assessments.

    Differences:
    The GWU qualification consists of both coursework comprising both elective and compulsory modules whereas the SA qualification consists of only thesis and of coursework.

    Country: Canada
    Institution: University of Waterloo
    Qualification: Doctor of Philosophy (PhD) in Statistics - Biostatistics
    Duration: Two years Full-Time
    Credits: 40 Credits

    Entry Requirements:
  • A Master's degree in statistics or actuarial science, completed or expected.
  • At least an overall 78% average from a Canadian university (or its equivalent).
  • An interview may be required.
  • Graduate research fields: Biostatistics, Computational Statistics, Probability, Statistical Theory and Methods.

    Qualification structure:
    The PhD in biostatistics curriculum is focused on devising solutions to public health problems through the development of five key competencies in every learner:
  • Applying innovative probabilistic and statistical theory and computing approaches to the development of new biostatistical or bioinformatics methods and publishing this original research in academic journals.
  • Providing leadership in the design, conduct, and analysis of collaborative research studies in medicine and public health.
  • Applying modern statistical and computational methods to effectively analyze complex medical and public health data, including the development of new software for nonstandard problems and simulation methods.
  • Collaborating and communicating effectively with research scientists in related disciplines.
  • Teaching biostatistics or bioinformatics effectively to health professionals, research scientists, and graduate students.

    Will be prepared for a high-impact career in academia or a research or leadership role in government or within the health care, pharmaceutical, or biomedical industries. Learners will also be positioned to play an important role in safeguarding public health and improving lives through quantitative research.

    Assessment:
    The PhD thesis examination, which is the culmination of the candidate's research efforts as a graduate student, is divided into two stages:
  • Departmental Thesis Presentation.
  • University Thesis Defence.

    Departmental Thesis Presentation: PhD students are required to present the results of their research before interested members of the department. This departmental thesis presentation is intended to fulfil several purposes. Learners have an opportunity to practice their presentation skills and gain valuable experience in answering questions about their work in a public setting. As well, faculty and graduate students who are interested in the thesis topic are provided with an overview of the student's research prior to the actual thesis examination.

    PhD Thesis Examination: the student shall defend the thesis in an oral examination before an Examining Committee, which shall consist of the supervisor(s), two faculty members in the Department, one faculty member from outside the Department, and an external examiner familiar with the student's research field. The committee is approved by the Faculty Graduate Committee.

    Similarities:
    The University of Waterloo (UoW) and the South African (SA) qualification requires applicants who completed master's degree in statistics.

    Differences:
  • The UoW qualification is offered over a minimum period of two years full time study whereas the SA qualification takes a minimum of three years of full-time study.
  • The qualification carries a weighting of credits whereas the SA qualification has 360 credits.

    Country: United States of America
    Institution: University of Cambridge, Barkley
    Qualification Title: Doctor of Philosophy (PhD) in Biostatistics
    Credits: 90
    Duration: Three years of full-time study.

    Entry Requirements:
    The University of Cambridge, Barkley (UCB) requires a master's degree in mathematics, statistics, or a related discipline.

    Purpose:
    Biostatistics is one of the most exciting areas of applied statistics - biostatisticians collaborate with scientists in nearly every area related to health and biology. Statistical models and methodologies have provided invaluable insight into the aetiology of AIDS, cancer, genetics, psychology, and numerous other areas of scientific research. The UCB qualification in Biostatistics trains biostatisticians to solve problems in the health sciences and develop biostatistical methodology. Training combines mathematical statistics, biostatistical methods and a third-field specialization. It is designed to train statisticians who can apply statistical methods to solve problems in the health field and who can conduct theoretical research in statistical methodology.

    PhD studies within the multi-disciplinary Medical Research Council (MRC) Biostatistics Unit include diverse training opportunities for all aspects of research and encourage the development of both academic and generic research skills. The MRC Biostatistics Unit places strong emphasis on the training of a new generation of biostatisticians, and on producing skilled researchers in this high demand area. This training is conducted in the innovative and interdisciplinary public health culture of the College of Public Health and Health Professions and the College of Medicine. Graduates will help address the shortage of biostatisticians around the world. The UC qualification enable learner to gain experience in written and oral presentation of thesis; monitor the quality of the research project; and ensure that the PhD project is on track.

    The demand for trained biostatisticians continues to increase as the world becomes more dependent on predictive data and numerical reasoning, particularly related to research in the health sciences.
    Those who earn a graduate degree in biostatistics, work in health care, biotech, and life sciences, using computer models to, for example, predict cancer growth in a cell. Many doctoral graduates accept faculty positions in schools of public health, medicine, and statistics and/or math departments at colleges and universities, both in the United States and abroad. Some graduates take research positions, including with pharmaceutical companies, hospital research units, non-profits, and within the tech sector

    Qualification structure:
    This program offers training in the theory of statistics and biostatistics, computer implementation of analytic methods and opportunities to use this knowledge in areas of biological/medical research. The resources of Berkeley Public Health and the UC Berkeley Department of Statistics, together with those of other university departments, offer a broad set of opportunities to satisfy the needs of individual students. Furthermore, the involvement of UCSF faculty from the Department of Biostatistics and Epidemiology also enriches instructional and research activities.

    A PhD degree in Biostatistics requires a program of courses selected from biostatistics, statistics, and at least one other subject area (such as environmental health, epidemiology, or genomics), an oral qualifying examination, and a thesis. Courses cover traditional topics as well as recent advances in biostatistics and statistics. Those completing the PhD will have acquired a deep knowledge and understanding of the MA subject areas. Since graduates with doctorates often assume academic research and teaching careers, a high degree of mastery in research design, theory, methodology, and execution is expected, as well as the ability to communicate and present concepts in a clear, understandable manner.

    The PhD degree program requires 4-6 semesters of coursework, and the completion of the qualifying examination and thesis (in total, a minimum of four semesters of registration is required). Since there are no formal course requirements for the PhD, a program of courses appropriate to a student's background and interests may be developed with a graduate adviser.

    The doctoral program in the Department of Biostatistics requires a minimum of 90 semester credits beyond the bachelor's degree. At least 30 of these credits must be directly related to statistics or biostatistics at the master's level (i.e. Master of Science in statistics or biostatistics).
    All students must complete a minimum of 54 credits of biostatistics/statistics course work (30 credits will typically be transferred from a Master of Science program), 6 credits of public health course work, 3 credits towards consulting requirement, 6 credits towards a cognate requirement, and 21 credits of thesis work.

    A minimum of 90 credits beyond the bachelor's degree is required for the doctoral degree. Formal course work accumulated by students should be in the neighbourhood of 60 credit hours. The remaining hours will be in PHC 7980 (thesis research).

    Compulsory Modules:
  • Biostatistics course, 12 Credits.
  • Public Health courses, 6 Credits.
  • Consulting requirement, 3 Credits.
  • Biostatistics/statistics electives, 12 Credits.
  • Cognate option or additional biostatistical/statistics electives, 6 Credits.
  • Biostatistics/Statistics, 30 Credits.
  • Thesis, 21 Credits.

    Assessment:
    The UCB qualification is assessed through a combination of formative and summative assessment methods.

    Formative assessment:
    Formative assessment consists of:
  • One-to-one supervision.
  • Seminars and classes.
  • Workshops.
  • Journal clubs and other discussion groups.
  • Posters and Presentations.
  • Feedback from supervisors during their regular one-to-one meetings.

    Summative Assessment:
    For the PhD degree, the thesis should not exceed 60,000 words (or 80,000 by special permission of the Degree Committee). This limit excludes figures, photographs, tables, appendices, and bibliography. Formatting should be one-and-a-half spaced and pages should be double-sided. Submission of the final thesis will be followed by an oral examination.

    All PhD learners are required to undergo formal assessment (by written report and viva) in the final quarter of their first year. If successful, the student moves from being "probationary" to being registered for the PhD and can proceed with their project. Further informal assessment via presentation takes place in the first term of year three.
    Many issues in the health, medical and biological sciences are addressed by collecting and exploring relevant data. The development and application of techniques to better understand such data is a fundamental concern of our program.

    Similarities:
  • Both the University of Cambridge Barkley (UCB) and the South African (SA) qualifications are offered over three years of full-time study.
  • The UCB and SA qualifications require a master's degree in mathematics, statistics, or a related discipline.
  • Both the UCB and SA qualifications are assessed through a combination of formative and summative assessment methods.

    On completion of both UCB and SA qualifications, graduates be able to:
  • Conduct independent research in the development of new biostatistical methodology.
  • Engage in successful collaborations with investigators in new quantitative fields.
  • Write statistical methodology papers for peer-reviewed statistical and biostatistical journals.
  • Write collaborative papers for peer-reviewed subject matter journals.
  • Compete successfully for research and teaching positions in academic institutions, federal and state agencies, or private institutions.

    Differences:
    The UCB qualification carries 90 credits, and the SA qualification has 360 credits.
    The UCB qualification consists of both coursework and the research project which culminates into a thesis.

    Country: United Kingdom
    Institution: University of Essex
    Qualification Title: PhD Bio-Statistics
    Maximum duration: Four years full time
    NQF Level: A postgraduate research degree is a level 8 qualification

    Entry requirements:
  • A good Honours degree and a master's degree in a relevant subject.
  • A well-developed research proposal is also essential.

    Purpose:
    PhD Biostatistics is an advanced research degree within the Department of Mathematical Sciences. Biostatistics carries out research in statistical analysis, such as survival analysis, longitudinal analysis, Bayesian statistics, analysis of biological and behavioural data and spatial statistics, with collaboration areas including clinical trials, genetics, infectious disease, and data visualisation.

    Qualification structure:
    A research degree gives you the chance to investigate an area or topic in real depth and develop transferable research skills. Learners have opportunities to attend conferences, publish papers, and give talks at departmental research seminars. You may also attend some university modules and will meet with your supervisor typically on a weekly basis. PhD students are usually encouraged to take the taught module, Research Methods, in the first year of study, so they are well equipped with the necessary skills to undertake effective research.
  • Occasional Study: Mathematics (Research).
  • Occasional Study: Mathematics.
  • Applied Mathematics.
  • Bioinformatics.
  • Biostatistics.
  • Mathematical Biology.
  • Mathematics.
  • Operational Research.
  • Pure Mathematics.
  • Statistics.
  • Actuarial Science.
  • Data Science.

    Assessment:
    A PhD, taking at least three years typically involves wide reading around the subject area in the first year, then gradually developing original results over the second and third years, before writing them up in a coherent fashion. The resulting thesis is expected to make a significant contribution to knowledge. PhD is awarded after successful defence of your thesis in an oral examination (viva), in which learners are interviewed about the research by two examiners, at least one of whom is from outside Essex.

    Similarities:
    Both the Essex University and the South African (SA) qualifications require applicants who have graduated master's degree in Mathematics, Statistics and Biostatistics and relevant fields.

    Differences:
    The Essex University qualification is registered at RQF Level 8 whereas the South African (SA) qualification is registered at NQF Level 10. 
    		•

    ARTICULATION OPTIONS 
    This qualification allows possibilities for both vertical and horizontal articulation.

    Horizontal Articulation:
  • Doctor of Philosophy in Mathematics, NQF Level 10.
  • Doctor of Philosophy in Biostatistics, NQF Level 10.
  • Doctor of Philosophy in Applied Statistics, NQF Level 10.
  • Doctor of Commerce in Mathematical Statistics, NQF Level 10.
  • Doctor of Philosophy in Statistics, NQF Level 10.

    Vertical Articulation:
  • Post-doctoral Degree. 
    		•

    MODERATION OPTIONS 
    N/A 

    CRITERIA FOR THE REGISTRATION OF ASSESSORS 
    N/A 

    NOTES 
    N/A 

    LEARNING PROGRAMMES RECORDED AGAINST THIS QUALIFICATION: 
     
    NONE 


    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.
     
    NONE 


    All qualifications and part qualifications registered on the National Qualifications Framework are public property. Thus the only payment that can be made for them is for service and reproduction. It is illegal to sell this material for profit. If the material is reproduced or quoted, the South African Qualifications Authority (SAQA) should be acknowledged as the source.