 Pravděpodobně máte vypnutý JavaScript. Některé funkce portálu nebudou funkční.
Course detail
Probability and Statistics I
Course unit code:  FSIS1P  

Academic year:  2016/2017  
Type of course unit:  compulsory  
Level of course unit:  Bachelor's (1st cycle)  
Year of study:  3  
Semester:  winter  
Number of ECTS credits:  5  



























Type of course unit:
Lecture:  26 hours, optionally 

Teacher / Lecturer:  doc. RNDr. Libor Žák, Ph.D. 
Syllabus:  Random events, field of events, and probability (properties). Conditioned probability and independent events(properties). Reliability of systems. Random variable (types, distribution function). Functional characteristics of discrete and continuous random variables. Numerical characteristics of discrete and continuous random variables. Basic discrete distributions A, Bi, H, Po (properties and use). Basic continuous distributions R, N, E (properties and use). Random vector, types, functional and numerical characteristics. Distribution of transformed random variables. Random sample, sample characteristics (properties, sample from N). Parameter estimation (point and interval estimates of parameters Bi and N). Testing statistical hypotheses. Testing hypotheses of parameters of Bi and N. 
seminars in computer labs:  26 hours, compulsory 
Teacher / Lecturer:  doc. RNDr. Libor Žák, Ph.D. 
Syllabus:  Descriptive statistics (onedimensional sample with a quantitative variable). Software Statistica. Descriptive statistics (twodimensional sample with a quantitative variables). Combinatorics. Probability (properties and calculating). Semester work assignment. Conditioned probability. Independent events. Written exam (3 examples). Functional and numerical characteristics of random variable. Functional and numerical characteristics of random variable  achievement. Probability distributions (Bi, H, Po, N), approximation. Random vector, functional and numerical characteristics. Written exam (3 examples). Point and interval estimates of parameters Bi and N. Testing hypotheses of parameters Bi and N. Testing hypotheses of parameters Bi and N  achievement. Tests of fit. Regression line, estimates, tests, and plots. 