Handbook

Linear algebra is a key tool in mathematics and its applications. Topics includevector spaces, linear transformations, change of basis, inner products, orthogonalization, least squares approximation, QR factorization, determinants, eigenvalues and eigenvectors, diagonalization, Jordan forms, matrix exponentials and applications to systems of differential equations, other applications of linear algebra.

Probability and statistics provide tools to apply and interpret statistical methods in an Engineering context and to build foundations for future courses in their programs. Topics include descriptive statistics, random variables and special probability distributions such as Binomial, Poisson, Exponential and Normal, sampling distribution and the Central Limit Theorem, statistical inference for proportions and means including confidence intervals and hypothesis testing, statistical analysis in the simple linear regression model and analysis of variance.
MATLAB will be used in the statistics part of the course as a tool for statistical computations and graphical and numerical illustration of theoretical concepts.

The course is delivered through a series of lectures and tutorials, where students can extend and refine their knowledge of the lecture material.