Mathematics and Statistics

The purpose of mathematical modelling is to describe the essential features of a phenomenon or a system in a manner which allows the use of various mathematical methods for a deeper analysis. This makes it possible to study for instance the time development of the system or the effect of changing the system parameters.

To formulate a mathematical model can be a challenging task. It requires both a solid understanding of the basic interactions governing the system under study and a good knowledge of mathematical methods. Most of the customers of CSC either use established mathematical models or develop new ones. Often the solution of the models is possible only through computer simulations or numerical methods.

Numerical methods

A good command of numerical methods is an essential requirement when mathematical models are used to simulate real-world problems on a computer. One must choose the right numerical and computational methods and programming tools for the given problem.

One must also be aware of the limitations of numerical methods and control the error sources. The numerical analysts of CSC assist researchers in solving both linear and nonlinear systems of equations, eigenvalue problems, differential equations, numerical integration and optimization problems, and various other tasks related to the processing of numerical data.

Moreover, the numerical analysts of CSC give courses in numerical methods and the use of mathematical software. Content of the courses will be tailored to meet the needs of the customer.

Statistics

Statistics is a discipline in which characteristics and qualities of natural phenomena are studied based on observation data sets. CSC's statisticians help researchers in the preprocessing of data, selecting the method of analysis, as well as on visualization and interpretation of the results.

The following mathematics and statistical analysis software are available for researchers.

Contact

In case of a question or problem, please contact CSC Service Desk.