Probability and Applied Statistics

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Software Engineering

Synopsis:

The lecture links to previous analogue courses with significant emphasis of relationship between mathematical models and practical aplication and warrant of inevitability of this relatonship

Requirements:

Syllabus of lectures:

1.Concept of statistical thinking, statistics as basic modern literacy and inevitability in research of real patterns and in all areas of aplication.

2.Plurality of „probability“ definitions. Areas of their aplications and use in modeling of problems in science, technics, economics and elsewhere.

3.Conditional probabilities, statistical independence, correlation, their interpretation in practical use.

4.Bayes attitude as one of basicla principals in evaluation of experimental material.

5.Punctual estimation in discreet and coherent case of random magnitude, through statistical characteristics.

6.Laws of big numbers and central limit theorem as a mathematical solution of formulation of definition of interval estimation, and their use in statistical research. 7.Testing of hypothesis as a specific way of thinking and evaluation of experimental material.

8.Regresive and correlational analysis as a specific way to find out connections, hidden in statistical experimental material.

9.Markov's chains ant stochastic processes as a mathematical model of real statistically depend ent phenomenons.

Syllabus of tutorials:

1.Concept of statistical thinking, statistics as basic modern literacy and inevitability in research of real patterns and in all areas of aplication

2.Plurality of „probability“ definitions. Areas of their aplications and use in modeling of problems in science, technics, economics and elsewhere.

3.Conditional probabilities, statistical independence, correlation, their interpretation in practical use.

4.Bayes attitude as one of basicla principals in evaluation of experimental material

5.Punctual estimation in discreet and coherent case of random magnitude, through statistical characteristics

6.Laws of big numbers and central limit theorem as a mathematical solution of formulation of definition of interval estimation, and their use in statistical research

7.Testing of hypothesis as a specific way of thinking and evaluation of experimental material

8.Regresive and correlational analysis as a specific way to find out connections, hidden in statistical experimental material

9.Markov's chains ant stochastic processes as a mathematical model of real statistically dependent phenomenons

Study Objective:

As one of the current literacy is the goal of the lemure to lead students to an independent ability to analyze, process and evaluate the statistical and experimental material is contemporary, modern scientific methods.

Study materials:

Key references :

KAREL ZVÁRA, JOSEF ŠTĚPÁN: PRAVDĚPODOBNOST A MATEMATICKÁ

STATISTIKA, MATFYZPRESS, UK, Grada 2006

Recommended references :

Jiří Anděl: Statistické metody, MATFYZPRESS, UK,Grada, 1998

Note:

Further information:

Course may be repeated

No time-table has been prepared for this course

The course is a part of the following study plans: