Mathematics

This course covers mathematics relating to differential equations. Topics include ordinary differential equations, systems of differential equations, Laplace transformations and applications, partial differential equations separable solutions, plane waves solutions, Bessel's Equation, Legendre's equation, dynamic systems and boundary eigenvalue problems. Techniques for solving differential equations are used in the context of application to fields of engineering.

This course offers an introduction to probability theory for students with knowledge of elementary calculus. The course covers not only the mathematics of probability theory but works through diverse examples to illustrate the wide scope of applicability of probability, such as in engineering and computing, social, and management sciences. Topics covered include counting methods, sample space and events, axioms of probability, conditional probability, independence, random variables, discrete and continuous distributions, joint and marginal distributions, conditional distribution, independence of random variables, expectation, conditional expectation, moment generating function, central limit theorem, and weak law of large numbers.

The course provides an introduction to the ideas underlying the calculation of risk from a Bayesian and frequentist standpoint, and the structure of rational, consistent decision making. It is primarily intended for third and fourth year undergraduate students and taught postgraduate students registered on the degree programs offered by the Department of Statistical Science.

This course examines the basic principles of engineering mathematics, calculation, and their practical applications in engineering. The course covers linear algebra (matrix, vector, determinant, linear equation system, matrix eigenvalue problem), vector calculus, vector divergence and curl, gradient and direction derivative function of scalar field, Fourier series analysis and integration, Conversion and other units.