Departments

About Us – Statistics Department

About Us

HISTORY OF THE DEPARTMENT

The Department of Statistics at Michael Okpara University of Agriculture has a rich history of development and specialization. It began as a small unit within the Department of Physical and Sciences in 1994, offering foundational service courses to various departments and colleges during the 1994/1995 academic session. Recognizing the demand for specialized statistical education, the university’s Senate approved the establishment of a degree program in Statistics in 1995. This milestone marked the beginning of a dedicated Statistics program, with the inaugural cohort of 10 students enrolled in the same year.

Over the years, the department underwent significant transformations. By the 2004/2005 academic session, the original Department of Physical Sciences was restructured into two distinct entities: the Department of Physics and the Department of Mathematics, Statistics, and Computer Science. In 2011, the department continued to evolve as the Senate approved further specialization, creating separate departments for Mathematics and Statistics and for Computer Science. This restructuring aimed to foster growth in each discipline, responding to the increasing academic and professional demand.

In March 2012, the journey towards specialization culminated with the establishment of the Department of Statistics as a distinct entity. By September 2013, the department had expanded considerably, with student enrolment reaching 276. Today, the Department of Statistics stands within the College of Physical and Applied Sciences, offering Bachelor of Science (B.Sc.) degree, Postgraduate Diploma (PGD), Master of Science (M.Sc.) degree, and Doctor of Philosophy (Ph.D.) degree in Statistics, supporting both academic growth and professional specialization for students at every level of statistical education. The department of Statistics now run degree programme in Statistics/Data Science.

OVERVIEW OF STATISTICS

Statistics/Data Science programme is designed to enable students acquire far-reaching knowledge in the management of data, including ways to gather, review, analyse, and draw conclusions from data. Throughout the course, students will gain experience in working as part of a team, and learn how to use specialized statistical software packages in analysis of big data. The students will also be exposed to data science and the use of artificial intelligence techniques in data analysis. Some of the areas that the students will be exposed in Data science includes data cleaning and pre-processing techniques, use of python software in data collection, supervised and unsupervised machine learning techniques and analysis as well optimization techniques in AI.

Students are given intensive exposure to probability and introductory statistical methods, introducing the ideas of likelihood and regression modelling. Other statistics topics that will be covered include experimental design, inference, computational inference, sampling and databases.

Statistics facilitates the decision-making process by quantifying the element of chance or uncertainties. The course is designed to develop concepts, from basic level to increasingly complex topics or skills. Graduates of the programme will acquire sufficient theoretical and practical knowledge to enhance sustainability of a better development and can compete favourably in any place.

 

 

PHILOSOPHY

The philosophy of the Statistics/Data Science programme is to provide broad based education in the use of a limited sample to make intelligent and accurate conclusions about a greater population. The use of tables, graphs, and charts will also play a vital role in presenting data being used to draw these conclusions.

OBJECTIVES

The objectives of the Program are to:

  1. develop in students a sense of enthusiasm for Statistics/Data Science, an appreciation of its application in different areas and to involve them in an intellectually stimulating and satisfying experience of learning and studying;
  2. provide students a broad and balanced foundation in Statistics knowledge and practical skills in data science;
  3. develop in students, the ability to apply their Statistics/Data science knowledge and skills to the solution of theoretical and practical problems in industry;
  4. develop in students, through an education in Statistics/Data science, a range of transferable skills of values in Statistics/Data science related and non-Statistics/Data science related employment;
  5. provide students with knowledge and skills- base from which they can proceed to further studies in specialized areas of Statistics/Data science or multi-disciplinary areas involving Statistics.

UNIQUE FEATURES OF THE PROGRAMME

The unique features of the programme include:

  1. more practical hours are dedicated to the use of statistical software and machine learning techniques for data collection and analysis ;
  2. Designing effective and proper planning of statistical inquiry and research in any field;
  3. independent student research projects allow students to explore topics of interest in great depth, and with the guidance of a faculty mentor; and
  4. entrepreneurship skill for the students and the industrial attachment which provides hands-on experience on industrial workflow and ethics and thereby enhancing employability.

 

EMPLOYABILITY SKILLS

  1. Graduates from the programme will be able to demonstrate: practical skills relating to solution of statistics problems express themselves in writing for professional and academic audience; analytical skills appraise key issues in both the descriptive and statistical inference.
  2. Students will also be able to synthesis concepts; ability to plan and execute, design and conduct surveys, construct and mange various criteria’s in decision making. Graduates of the program will be employable in schools, ministries, departments and agencies. They may also be self-employed or even employers of labour.

The 21st Century Skills required for application of statistics in the field include

  1. Data analysis
  2. Information literacy
  3. Productivity
  4. Collaboration
  5. Innovation
  6. Technology Literacy
  7. Critical Thinking
  8. Creativity

 

 

 

 

JOB/CAREER OPPORTUNITIES

Many government organizations and agencies hire Statisticians to evaluate social, demographic, and economic measurements. Many other environmental, scientific, and agricultural agencies hire Statisticians for similar type of work in their respective fields.

Some of the careers include:

  • Statistician, Lecturer, Professor, Content Analyst, Statistic Trainer, Data Scientist, Consultant, Analyst, Auditor, Actuary, Algorithm Designer, Computer Scientist,  Consultant, Data Miner, Database Administrator, Economist, Financial Analyst or Advisor, Insurance Underwriter, Inventory Analyst, Market Researcher, Mathematician, Research Analyst, Social Scientist, Statistical Engineer, Survey Researcher, Biostatistician.