Course detail

Mathematics 3

FEKT-BMA3Acad. year: 2012/2013

Numerical mathematics: numerical errors, functional approximation, interpolation and splines, least squares method, numerical derivation and integration, numerical solving of differential equations.
Probability: events and probabilities, conditional probability, independent events, the Bayes theorem, random variable, probability distributions (chosen types), standard normal distribution.
Mathematical statistics: statistical measures, tests.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

Mgr. Irena Hlavičková, Ph.D.

Department

Department of Mathematics (UMAT)

Learning outcomes of the course unit

After the completion of the course the students should be able to solve equations and systems of equations numerically, use the least squares method and interpolation, numerical derivation and integration formulas as well as solve some types of differential equations numerically.In the area of probability they should know where to use specific probabilistic models. Some statistical test are also considered.

Prerequisites

The knowledge of combinatorics on the secondary school level, BMA1 and BMA2 courses.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

Written examination is evaluated by maximum 70 points, the student's work during the semestr is assesed by maximum 30 points.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

Subject comprises of two mathematical disciplines: NUMERICAL METHODS whose objective is to introduce fundamentals of numerical problem solving, and PROBABILITY whose purpose is to consider probabilistic techniques in problem solving.

Specification of controlled education, way of implementation and compensation for absences

The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

FAJMON, B., RŮŽIČKOVÁ, I. MATEMATIKA_3_S. PDF. Matematika 3. Brno: UMAT FEKT VUT, 2003. s. 1 ( s.) (CS)
Hlavičková, I., Hliněná, D.: Matematika 3 - sbírka úloh z pravděpodobnosti. Elektronický text FEKT VUT, Brno, 2010 (CS)
Novák, M.: Matematika 3 - sbírka příkladů z numerických metod. Elektronický text FEKT VUT, Brno, 2010 (CS)

Recommended reading

Haluzíková, A. Numerické metody. Skriptum FEI VUT. Brno: VUT, 1989. (CS)
Zapletal, J. Základy počtu pravděpodobnosti a matematické statistiky. Skriptum FEI VUT. Brno: PC-DIR, 1995. (CS)

Classification of course in study plans

  • Programme EECC Bc. Bachelor's

    branch B-AMT , 2 year of study, winter semester, compulsory
    branch B-MET , 2 year of study, winter semester, compulsory
    branch B-TLI , 2 year of study, winter semester, compulsory
    branch B-SEE , 2 year of study, winter semester, compulsory
    branch B-EST , 2 year of study, winter semester, compulsory

  • Programme EEKR-CZV lifelong learning

    branch EE-FLE , 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. RNDr. Jan Chvalina, DrSc.
Mgr. Irena Hlavičková, Ph.D.

Syllabus

1. Banach theorem. Jacobi and Gauss-Seidel iterative methods.
2. Interpolation, least squares method.
3. Spline, numerical methods of differentiation.
4. Numerical integration - trapezium and Simpson methods.
5. Solving ODE - Euler method and modifications of the method. Runge - Kutta method.
6. Solving ODE - Euler method for a system of equations, shooting method, finite difference method. Multistep methods.
7. Probabilistic models (classical and geometrical probabilities, discrete and continuous random variables).
8. Expected value and dispersion.
9. Binomial distribution. Fundamentals of statistical tests. The sign test.
10.Poisson and exponential distributions. Their application in queueing theory.
11.Normal distribution. Central limit theorem. Approximation of binomial distribution by means of normal distribution. Z-test and power.
12.The mean expected value test.

Exercise in computer lab

14 hod., compulsory

Teacher / Lecturer

Mgr. Jiří Vítovec, Ph.D.
Mgr. Irena Hlavičková, Ph.D.
Mgr. Martin Tůma, Ph.D.

Syllabus

1. Root separation, bisection, regula falsi.
2. Iterative metod, Newton method.
3. Systems of nonlinear equations, interpolation.
4. Spline, least squares method.
5. Numerical differentiation and integration.
6. Numerical methods for ordinary differential equations - Euler method, Runge - Kutta method, finite difference method.
7. Classical and geometrical probability.
8. Discrete and continuous random variable.
9. Expected value and dispersion.
10. Binomial distribution. The sign test.
11. The Poisson and exponential distributions, queuing theory.
12. Uniform and normal distributions, binomial approximation of normal distribution, z-test.
(13. Mean expected value test, power.)