Probability and Applied Statistics
Code  Completion  Credits  Range  Language 

18AST  Z,ZK  3  1+1  Czech 
 Lecturer:
 Jana Sekničková
 Tutor:
 Jana Sekničková
 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
 Timetable for winter semester 2020/2021:
 Timetable is not available yet
 Timetable for summer semester 2020/2021:
 Timetable is not available yet
 The course is a part of the following study plans:

 Aplikace softwarového inženýrství (compulsory course of the specialization)