Vision, Mission and Mandate
- To be the centre of excellence in teaching mathematics for technological development.
Our Mission statement:
- To provide mathematical skills and create positive attitudes that cultivate a culture of research and professionalism to satisfy industrial and technological demands both nationally and internationally.
- To provide an opportunity to many students who wish to pursue different areas of mathematics by increasing their level of competence and preparing them adequately to enable them join the job market.
- To provide mathematical skills and positive attitudes that cultivate a culture of research and professionalism to satisfy industrial and technological demands both nationally and internationally.
In order to fulfill the training needs as stipulated in the Kenya Polytechnic University College Legal order the School of Mathematics and Statistics has embarked on developing demand driven curriculums. To this end we have developed and implemented the following Diploma and Degree courses.
• Diploma in Actuarial Science with computing
• Diploma in Applied Statistics with Computing
• Bachelor of Science (Mathematics)
• Bachelor of Technology in Applied Statistics
• Bachelor of Philosophy in Technology in Applied Statistics.
School of Mathematics and Statistics
Mathematics is an academic discipline and a body of knowledge that involves the study of concepts such as quantity, structure, space and change. It is an essential tool in many fields including natural science, engineering, Medicine and Social Science such as Economics and Commerce. The School of Mathematics and Statistics offers programmes in mathematics and Statistics and comprises of four Departments: The School trains students in the fields of Mathematics and Statistics with a view to applying the knowledge gained to various fields in a practicable way. Major fields of mathematics includes Pure mathematics, Applied Mathematics and Statistics. Specialized disciplines taught within the departments include actuarial science, applied statistics, applied information economics, biostatistics, business statistics, quantitative methods, data analysis, data mining, demography, econometrics, statistical modelling, structured data analysis (statistics) and survival analysis.