Syllabus
Ten modules that correspond to the modules of the lessons from mathematical inferences (MB162P05) are offered to the students during the practice. The practices are not mandatory; however, one cannot attend the practices without attending the lessons.
The practice will be run on the former students’ request, therefore we recommend them to your attention.
Notation: basic skills in mathematical notation; how to solve and simplify equations and inequations with respect to the question in focus.
Function 0: link between formal notation and graphical pattern for selected functions.
Recurrence relations and differential equations: training in function derivatives and its graphical representation.
Integration: training in function integration and graphical representation of integrals.
Functional equations: training in functional and differential equations.
Logarithm: training in logarithms; practice in the reading of the biological texts with logarithms in it.
Invariances: practice in the reading of the biological texts with invariance in it.
Functions 1: training in the function of multiple variables; simple calculations.
Statistical methods: practice in usage of mean, median, modus, maximum likelihood and multivariable statistical methods.
Transformations: transformation of a dataset, graphic representation of a function and frequency distribution; case studies.
Matrices: practice in matrices calculus; determinant and eigenvalues of a matrix; how to use matrices when one solves a system of linear equations.
Annotation
The practice from mathematical inferences will support students to follow the lessons from mathematical inferences (MB162P05) and solve practical tasks (e.g., practice in computational skills) under professional tutoring.
The practice is not mandatory, but recommended, for it will be held on request of the former attendants of the lessons. One cannot, however, attend the practice without attending the lessons. We will also do our best to prepare the students on the next lesson during the practice. The students will be split into two groups, so that the lecturer will be able discuss the topics with each student personally. For further details see the annotation of
MB162P05.