Statistical Science

Programme Overview

The BSc in Statistical Science is designed to expose students to modern statistical theory and the various applications of statistics. Throughout the programme, there will be emphasis on laboratory-based work and problem-based learning via statistical modelling, computer programming, analysing and interpretation of real world problems.

Each course in the programme is of both a theoretical and practical nature exposing the students to different techniques and methodology of statistics that are used in society. Illustrative examples will be taken from different disciplines that require statistics.

Research and Development is often considered as one of the driving forces behind growth and job creation. 

Additionally, the programme is aimed to further develop critical and analytic thinking skills and will aid in interpreting data, normally published in today’s scientific journals. 

Programme Objectives

The programme is aimed to:
•    Prepare graduates for careers in, but not limited to-: the financial, health, agriculture, government, business, telecommunication and transportation industry;
•    Prepare students to undertake further study at the graduate level;
•    Familiarise students with computational techniques and            software typically used in the statistical arena;
•    Provide a good grounding in the best practice of collating           and disseminating information;
•    Construct practical statistical models for several processes        in the real-world; 
•    Assess the use of statistical models;
•    Emphasise transferable skills e.g. team work, solve                 problems quickly and seamlessly, organise and manage           your time effectively, communicate, adapt and innovate           and much more.


Admission Requirements

In order to do the Mathematics Degree, candidates must satisfy the requirements for entrance to the Faculty of Science and Technology they must:

1.    Satisfy the University requirements for Normal Matriculation.
2.    Have obtained passes at CSEC Secondary Education General Proficiency level (or     equivalent) in Mathematics and two subjects at CAPE (both comprising Units 1 & 2) or at     GCE A-level (or equivalent) one of which must be an approved science subject.

1.    Satisfy the University requirements for Lower level Matriculation. 
2.    Have obtained passes at CSEC Secondary Education General Proficiency level with     grades I, II, or since 1998 grade III (or equivalent) in Mathematics and two approved     science subjects.


Programme Structure

In addition, a minimum of 9 additional Level I credits within the University 
Year 2: Twenty-four (24) credits as follows:
Semester I    

  • MATH2401: Elements of Mathematical Analysis   
  • MATH2410: A First Course in Linear Algebra    
  • MATH2404: Introduction to Probability Theory    
  • STAT2001: Inferential Statistics

Semester II

  • MATH2407: Stochastic Modelling
  • STAT2002: Discrete Statistics*
  • STAT2003: Linear Models*
  • STAT2004:Multivariate Method*

Year 3: Twenty-four (24) credits as follows:
Semester I    

  • STAT3001: Regression Analysis**    
  • STAT3003: Design & Analysis of Experiments*

Semester II

  • STAT3002: Time Series**
  • MATH3423: Research Project**


Plus 12 credits from the following elective courses below:

Level II
MATH2403 - Multivariable Calculus
MATH2430 - Linear Optimization
MATH2411 - Introduction to Abstract Algebra 
MATH2431 - Non-Linear Optimization 
MATH2420 - Ordinary Differential Equations
MATH2701 - Financial Mathematics I 
MATH2421 - Fourier Series and Integral
MATH2702 - Actuarial Mathematics I

Level III
MATH3400 - Complex Variables
MATH3801 - Financial Mathematics II
MATH3410 - Advanced Linear Algebra 
MATH3802 - Evaluation of Actuarial Models
MATH3414 - Selected Topics in Operations Research
MATH3803 - Models for Financial Economics

MATH3421 - Partial Differential Equations 
MATH3804 - Actuarial Mathematics II
MATH3422 - Mathematical Modelling
MATH3805 - Mathematics of Pension Funds
MATH3424 - Numerical Methods
MATH3806 - Topics in General Insurance


Careers after Graduation

The career paths are limitless, but to name a few, such as teaching, financial services, telecommunication, environment, government, health, research and development, and transportation.

Further information
Statistics is used in many different jobs. There is therefore an ongoing need for good, well-trained Statisticians/Statistical Analysts to fill these jobs and perform the statistical work to a high standard as well as requiring a high standard of education in schools. This means that good statistical education in universities is of paramount importance.