DEPARTMENT OF STATISTICS

About the Department

The Department of Statistics is one of the academic units in the College of Social Sciences (CoSS). It was established in 1967 under the former faculty of Arts and Social Sciences and now in the College of Social Sciences. It was established to serve other departments of the mother faculty and other units within the university. In 1971/72 the department enrolled its own first batch of undergraduate students pursuing a Bachelor of Arts degree majoring in Statistics. Later in 1974 the department started to offer Master of Arts in Statistics and the first enrolment in PhD programme was in 1980. Members of staff are occupying offices in several locations whereas many members are located at Yombo 4/5 offices, few of them occupy offices in other buildings.

The department offers a number of courses to undergraduate and postgraduate students. The undergraduate programme in the department leads to the degrees of Bachelor of Arts in Statistics, B.A. (Statistics). Also it offers courses in the College of Social Sciences, College of Natural and Applied Sciences (CoNAS), College of Informatics and Communication Technologies (CoICT). The graduate Programmes consist of courses leading to Master of Science in Statistics MSc. (Statistics) and Doctor of Philosophy (PhD).

Departmental Vision

To become a leading department in training competent statisticians (Academic staff and non-academic in various institutions) who can handle data revolutionary innovations. 

​​​​​​​Departmental Mission

The mission is to transmit knowledge in both theoretical and applied statistics by developing and utilizing efficient training methods that will produce real time data, incorporate modeling techniques and focus on modern analytical methods.

The mission will be very much facilitated through:

Highly trained and motivated staff with PhDs working under enabling environment

• Well planned opportunities for long and short term training for staff
• Well planned and assured exchange programmes
• Availability of modern teaching and research facilities
• Attractive emoluments to enable retention of staff
• Provide clear guidelines on the roles of administrative staff and academic staff to serve the core mission of the University.

Blended learning and teaching methodology

• developing a comprehensive e-learning programme
• combining e-learning, webinars and face-to-face statistical training
• involving external teaching/seminars on new professional topical issues. 
• improving teaching infrastructure – Human resources, technologies and physical infrastructure (e.g. phasing out of the blackboard)

Robust network / cooperation with other institutions

• setting up new collaborations and improving existing links among universities, organizations and institutions at national, regional and international level
• Establishing themes that address social-economic problems that will enhance the institution’s reputation and subsequently attract external funding and consultancies

Digital Transformation

• Designing information flow infrastructure to support administrative work,  academics and  research – application of modern technologies

Academic contributions to society (Social Contributions)

• Encouraging development research and giving support to practical studies in order to strengthen policies and practice
• Encouraging efficient and effective use of statistical methods in research in order to improve the impact of research activities in policy and practices

Specific agenda:

Blended learning and teaching methodology

• Involve external teaching/seminars on new professional topical issues.
• Strategize on data practice at work place

Academic contributions to society (Social Contributions)

• Encourage development research and support practical studies in order to strengthen policies and practice
• Encourage efficient and effective use of statistical methods in research in order to improve the impact of research activities in policy and practices. In particular, through one of its applied Statistics courses, the Department is to follow up the idea of the National Village Register to assess the current data needs and determine the kind of elementary statistical skills to be imparted by the department at the grassroots
• Establish information communication tostrengthen linkage/co-ordination between the Department of Statistics and the relevant villages to improve plan implementation towards achieving the set developmental objectives.
• Enhance statistical information dissemination to the grassroots through such avenues as committee meeting method, rallies and public meetings, training and seminars, newsletters, and regular statistical leaflets.

Programmes

Undergraduate Programmes

​​​​​​​Postgraduate Programmes

The Department offers the following postgraduate Programmes;-

Mode of Study

This is a full time program at UDSM and is conducted during normal semester time.  Examinations are taken at the end of every semester for the courses taken that semester. The University and College of Social Sciences examinations rules and regulations for the degree programmes apply.

Entry Requirements

Undergraduate Programmes

Entry requirements in undergraduate program in the Department require a minimum of at least two principal passes of the advanced certificate of Secondary Education Examination (ACSEE), one of which must be in Advanced Mathematics.​​​​​​​

Postgraduate Programmes

The entry qualification for a master’s programme by coursework and dissertation requires a person to have at least a Lower Second Class degree (GPA of 2.7) or its equivalent from a recognized institution of higher learning.

Doctor of Philosophy (PhD) programme requires an applicant to possess at least Lower Second Class degree from the University of Dar es Salaam or any other recognized University by TCU with background of Statistics, Epidemiology and Biostatistics.

Courses Mapping

Shaded totals represent the minimum required credits per semester. A student may choose one additional optional course from the list provided under a relevant semester and not from elsewhere. Compulsory-year Practical Training (AS 299) is conducted for 8 weeks during the long vacation.