About the Programme|
Mathematical sciences is a broad term that includes, in addition to areas of mathematics, those academic disciplines that are primarily mathematical in nature but may not be universally considered subfields of mathematics proper. Apart from analytical and reasoning skills, together with problem-solving skills, acquired through the learning of rigorous mathematical concepts, students will also be able to pick up computing skills, technical communication techniques, as well as have the opportunity to learn how mathematics is connected with other disciplines such as biology, computer science, economics and finance. Opportunities for deeper investigations in the subject are also provided for students who seek extra challenge through special courses, supervised independent study and research projects. Given the broadness of mathematical sciences, in the first two years, students take common core courses in fundamental topics: calculus, linear algebra, discrete mathematics, probability, scientific programming and mathematical exposition, to build a strong foundation that will give them maximum flexibility and choices in later years. Subsequently, students will focus on one of the distinct specializations: Mathematics, Statistics and Actuarial Science.
Objectives
The objectives of this programme are to:
• Equip the learner with a solid mathematical foundation.
• Prepare learners for postgraduate training and research in mathematics.
• Prepare learners for a career in scientific, banking or business areas requiring mathematical or statistical background.
Programme Courses
| Year 1: Semester 1 | |
| MMA 100 | Basic Mathematics |
| MMA 109 | Foundation of Pure Mathematics |
| MMA 111 | Introduction to Calculus |
| MAS 101 | Descriptive Statistics |
| MAS 103 | Introduction to Probability Theory |
| MAC 107 | Introduction to Actuarial Science |
| MIT 101 | Basic Concepts of IT |
| MIT 103 | Web Browsing and Communication |
| MAC 105 | Microeconomics |
| Year 1: Semester 2 | |
| MMA 101 | Analytical Geometry |
| MMA 103 | Linear Algebra I |
| MMA 110 | Foundation of Applied Mathematics |
| MAS 102 | Probability and Distribution Theory I |
| MAC 102 | Fundamentals of Actuarial Methods I |
| MAS 106 | Introduction to Biostatistics |
| MAC 104 | Linear Models and Forecasting |
| MAC 106 | Macroeconomics |
| MIT 103 | Handling Data |
| MIT 104 | Descriptive Statistical Analysis and Presentations. |
| PHT 112 | HIV/AIDS |
| Year 2: Semester 1 | |
| MMA 202 | Vector Analysis |
| MMA 215 | Calculus |
| MMA 217 | Numerical Convergence |
| MMA 203 | Classical Mechanics |
| MMA 221 | Introduction to Number Theory |
| MAS 201 | Sample Surveys |
| MAS 203 | Economic Statistics |
| MAS 207 | Probability and Distribution Theory II |
| MAC 201 | Financial Mathematics II |
| MAC 203 | Fundamentals of Actuarial Mathematics II |
| MIT 201 | Statistical Computing I |
| MIT 203 | Collecting and Organising Data |
| Year 2: Semester 2 | |
| MMA 201 | Linear Algebra II |
| MMA 206 | Algebraic Structures |
| MMA 204 | Dynamics I |
| MMA 208 | Introduction to Analysis |
| MMA 216 | Multivariable Calculus |
| MMA 219 | Graph Theory |
| MAS 202 | Principles o Statistical Inference |
| MAS 204 | Demography and Social Statistics |
| MAC 202 | Life Testing Analysis |
| MAC 204 | Theory of Interest |
| MAC 206 | Actuarial Mathematics I |
| MAC 208 | Risk Theory |
| MAC 210 | Investment and Asset Management I |
| MIT 202 | Data Management |
| MIT 204 | Scientific Report Reading, Writing and Presentation |
| Year 3: Semester 1 | |
| MMA 300 | Real Analysis I |
| MMA 301 | Ordinary Differential Equations I |
| MMA 307 | Methods I |
| MMA 308 | Fluid Mechanics I |
| MMA 319 | Numerical Mathematics I |
| MAS 303 | Estimation Theory |
| MAS 305 | Stochastic Processes I |
| MAS 307 | Theory of Sampling Techniques |
| MAS 309 | Time Series Analysis and Forecasting |
| MAS 311 | Statistical Demography I |
| MAS 313 | Principles of Econometrics |
| MAS 315 | Statistical Genetics |
| MAC 303 | Actuarial Mathematics II |
| MAC 305 | Pension Mathematics |
| MIT 301 | Computer based Survey Techniques |
| MIT 303 | Computers applied to Mathematics |
| Year 3: Semester 2 | |
| MMA 302 | Linear Algebra III |
| MMA 303 | Complex Analysis I |
| MMA 304 | Group Theory I |
| MMA 309 | Real Analysis II |
| MMA 312 | Operations Research I |
| MAS 302 | Mathematical Methods |
| MAS 304 | Test of Hypothesis |
| MAS 306 | Statistical Modelling |
| MAS 308 | Analysis of Experimental Designs I |
| MAS 310 | Stochastic Decision Models I |
| MAS 312 | Statistical Computing II |
| MAS 314 | Research Methodology |
| MAC 300 | Financial Mathematics II |
| MAC 302 | Methods of Actuarial investigations |
| MAC 304 | Actuarial life contingencies I |
| MAC 306 | Financial economics |
| MIT 302 | Statistical Computing II |
| MIT 304 | Introduction to Object Orientated programming |
| MIT 306 | Web design Project |
| Year 3: Semester 3 | |
| MAS 317 | Industrial Attachment |
| Year 4: Semester 1 | |
| MMA 401 | Ring Theory |
| MMA 403 | Topology I |
| MMA 404 | Complex Analysis II |
| MMA 405 | Partial Differential Equations |
| MMA 409 | Differential Geometry |
| MMA 413 | Methods II |
| MMA 417 | Group Theory II |
| MMA 420 | Operation Research II |
| MAS 401 | Further Distribution Theory |
| MAS 403 | Non Parametric methods |
| MAS 405 | Analysis of Experimental Designs II |
| MAS 407 | Further Time series Analysis |
| MAS 409 | Further Sample Survey Theory and Methods |
| MAS 411 | Stochastic Decision Models II |
| MAS 413 | Stochastic Models for Biological Processes |
| MAS 415 | Biometric Models |
| MAS 417 | Statistical Demography II |
| MAS 419 | Econometric Models I |
| MAS 421 | Stochastic Processes II |
| MAS 423 | Practical Statistics |
| MAS 425 | Labour Dynamics |
| MAS 427 | Agricultural Indices |
| MAS 429 | Energy Analysis |
| MAS 431 | Teaching of Statistics |
| MAC 401 | Mathematics of Demography and Graduation |
| MAC 403 | Actuarial life contingencies II |
| MAC 405 | Investment and Asset Management II |
| MAC 407 | Principles of financial Management |
| MAC 409 | Project in Actuarial science |
| MAC 415 | Survival analysis |
| MIT 401 | Bayesian Modelling |
| MIT 403 | Writing Micros |
| MIT 405 | Programming: Advanced Objects and Data Structures |
| Year 4: Semester 2 | |
| MMA 402 | Measure Theory |
| MMA 407 | Field Theory |
| MMA 408 | Topology II |
| MMA 410 | Functional Analysis |
| MMA 411 | Partial Differential Equations II |
| MMA 414 | Fourier Analysis |
| MMA 416 | Galois Theory |
| MMA 418 | Algebraic Geometry |
| MMA 429 | Operations Research III |
| MAS 402 | Bayesian Inference and Decision Theory |
| MAS 406 | Robust Methods and Non-Parametrics |
| MAS 408 | Multivariate Methods |
| MAS 410 | Statistic Model Building |
| MAS 412 | Stochastic Models for social Processes |
| MAS 414 | Survey Research Methods |
| MAS 416 | Quality Control Methods |
| MAS 418 | Applied Population Analysis |
| MAS 420 | Applied demography |
| MAS 422 | Econometric Models II |
| MAS 424 | Applied Econometrics |
| MAS 426 | Statistical Computing III |
| MAS 428 | Response Surface Methodologies |
| MAS 430 | Educational Statistics |
| MAS 432 | Health Indicators |
| MAS 434 | Government Financial Structure |
| MAS 436 | Environmental / Ecological Indicators |
| MAS 438 | Statistical Organization |
| MAC 404 | Computational Finance |
| MAC 406 | Risk and Credibility Theory |
| MAC 408 | Risk Mathematics |
| MAC 410 | Fundamentals of General Insurance |
| MIT 402 | Problem based Statistical Analysis |
| MIT 404 | Algorithms |
| MIT 406 | Programming Project |
Programme Requirements
Admission Requirements
Applicants eligible for admission into the program must:
• Satisfy the minimum entry requirements for admission to the University and the School of Mathematics, Statistics and Actuarial Science.
• Attain a B-(minus) in Mathematics at KCSE or equivalent.
Duration of the Programme
The duration of the program shall normally be four (4) academic years.
Teaching methods in all units shall include lectures, seminars, tutorials, discussions.
Degree Structure
The program offers courses within the degree structure spelled out by the Faculty.
Course Structure
• The Department offers courses in terms of units as defined by the faculty.
• There shall be CORE, ELECTIVE and REQUIRED courses. Core courses are mandatory, while Elective and Required courses may be chosen by students as preferred in fulfilling the full-time load requirement.
• A student will take a minimum of 14 and a maximum of 16 units in each year of study. Students wishing to take more than 16 units will require Senate approval.
• There shall be an industrial attachment at the end of third year.