Bachelor of Commerce Honours in Business Statistics

Purpose

The purpose of the qualification is to equip students with a high level of theoretical engagement and intellectual independence with regard to relevant aspects of Business Statistics and thereby consolidate and deepen the student's expertise in this field. Furthermore, the student will come to understand the important role of research in the world of business, particularly in Business Statistics, and will be trained to perform authentic evaluations and independent research under supervision, aimed at actual and relevant problems in this field of expertise. The qualification aims to foster progressive thinking in Business Statistics, by developing a cadre of scholars with a wider and deeper understanding of this field of specialisation. This qualification prepares candidates for further postgraduate studies at Master's level and beyond, specifically in the field of Business Statistics.

Rationale

It is widely accepted that South Africa has a shortage of well-trained, critically thinking scientists who are capable of proceeding towards independent, high quality research. This qualification is aimed at providing South Africa with significant numbers of graduates who are able to undertake advanced research under the guidance of an expert through the acquisition of the necessary research skills and tools in the specific field of Business Statistics. These young scientists will ensure the broadening of the local leadership base of innovative and knowledge based economic and scholarly activity. The second rationale of this qualification is to provide students with the necessary knowledge, specific skills, applied competence and professional attitude in the field of Business Statistics to utilise the opportunities for continued personal intellectual growth, gainful economic activity and rewarding contributions to society.

Recognition of Prior Learning (RPL)

An applicant who cannot provide formal proof of compliance with the prescribed admission requirements for the Bachelor of Science Honours in Business Statistics, but with prior learning and relevant work experience may be admitted to the Honours Degree study after the procedure for Recognition of Prior Learning in terms of the University's RPL policy has been completed successfully. Such recognition is within the sole discretion of the University and within the context of faculty requirements. This qualification requires that the entrant will already have a Bachelor of Science (BSc) or an equivalent standard qualification in the field of Business Statistics at the North West University (NWU) or other University or equivalent institution. The North-West University subscribes to the principles underlying outcomes-based, source-based and lifelong learning. In this context, considerations of articulation and mobility play an important role. The NWU endorses the view that Recognition of Prior Learning (RPL) constitutes an essential element in deciding on admission to and awarding credits in an explicitly selected teaching-learning programme at honours level. RPL does not only imply assessment to determine the level of skills and knowledge comparable to Level 7 the candidate already possesses, but also the skills and knowledge the candidate has to master additionally prior to being accepted for the honours qualification. The assessment processes involved with RPL are the same as those followed for awarding credits in the formal graduate setting. An RPL candidate seeking credits for previously acquired skills and knowledge, must still comply with all the requirements as stated for modules, programmes and qualifications. The difference lies in the route of the assessment, since RPL assessment may be holistic in nature taking the context of the programme as well as the prior knowledge and experience of the person who is being assessed into account.

Entry Requirements

To be admitted to the qualification a student should have a Bachelor of Commerce (B.Com) with specialisation in Statistics Degree or its equivalent, with an average of at least 60% in third year.

This qualification comprises compulsory and elective modules, Level 8.

Compulsory Modules

• Multivariate Analysis (STFM613) Level 8 15 Credits.
• Applied Regression Analysis (STFM616) Level 8 15 Credits.
• Research Project (STFM671) Level 8 30 Credits.

Elective Modules

• Advanced Probability Theory (STFM612) Level 8 15 Credits.
• Statistical Quality Control (STFM614) Level 8 15 Credits.
• Decision Theory (STFM615) Level 8 15 Credits.
• Design Of Experiments and Sampling (STFM621) Level 8 15 Credits.
• Stochastic Models (STFM611) Level 8 15 Credits.

• Demonstrate advanced knowledge of computational scientific principles, bodies of content and conceptual issues.
• Understand the techniques and strategies involved in scientific enquiry and computing problem-solving.
• Think critically and creatively, while working as an individual, in teams and in multidisciplinary environments, showing leadership and performing critical functions.
• Communicate effectively, both orally and in writing, with scientific and lay audiences and be computer literate.
• Understand the professional and ethical basis of scientific enquiry, identify and analyse problems in computer based systems, execute research work, interpret collected data and information in scientific literature of computer development and programming, and be competent to report in detail on such work.

The following Associated Assessment will be assessed in an integrated manner across the Exit Level Outcomes

• A systematic and integrated knowledge and understanding of, and an ability to analyse, evaluate and apply the fundamental terms, concepts, facts, principles, rules and theories.
• Ability to apply appropriate discipline-related methods of scientific inquiry and independently validate, evaluate and manage sources of information.
• Critical reflection on, and understanding and application of, appropriate methods or practices to resolve complex discipline-related problems and thereby introduce change within related practice.
• Professional and ethical behaviour within an academic and discipline-related environment, with sensitivity towards societal and cultural considerations.
• Ability to effectively communicate scientific understanding and own opinions/ideas in written or oral arguments, using appropriate discipline-related and academic discourse as well as technology.
• Effective functioning as a member and/or leader of a team or a group in scientific projects or investigations, with self-directed management of learning activities and responsibility for own learning progress.

Integrated Assessment

Continuous formative assessment strategies in the form of assignments, tests, semester tests etc. are employed as well as integrated summative assessments in the form of formal examinations and a mini dissertation/project report etc. Oral presentations of smaller integrated research projects in individual as well as group context may also be employed. Students are continuously assessed on the application of integrated knowledge and advanced skills in order to assure that they are competent for the work place.