Course detail
Statistical Analysis
FSI-9STAAcad. year: 2024/2025
The course is intended for the students of doctoral degree programme and it is concerned with the modern methods of statistical analysis (random sample and its realization, distribution fitting and parameter estimation, statistical hypotheses testing, regression analysis) for statistical data processing gained at realization and evaluation of experiments in terms of students research work.
Language of instruction
Czech
Mode of study
Not applicable.
Guarantor
Department
Entry knowledge
Rudiments of the probability theory and mathematical statistics.
Rules for evaluation and completion of the course
The exam is in form read report from choice area of statistical methods or else elaboration of written work specialized on solving of concrete problems.
Attendance at lectures is not compulsory, but is recommended.
Attendance at lectures is not compulsory, but is recommended.
Aims
The objective of the course is formalization of stochastic thinking of students and their familiarization with modern methods of mathematical statistics and possibilities usage of professional statistical software in research.
Students acquire higher knowledge concerning methods of mathematical statistics, which enable them to apply stochastic models of technical phenomena and processes by means calculations on PC.
Students acquire higher knowledge concerning methods of mathematical statistics, which enable them to apply stochastic models of technical phenomena and processes by means calculations on PC.
Study aids
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
Anděl, J.: Základy matematické statistiky. Praha: Matfyzpress, 2011. (CS)
Meloun, M., Militký, J.: Kompendium statistického zpracování dat. Praha: Academia 2002. (CS)
Montgomery, D. C. - Renger, G.: Probability and Statistics. New York : John Wiley & Sons, Inc. 2010. (EN)
Ryan, T. P.: Modern Regression Methods. New York : John Wiley, 2004. (EN)
Meloun, M., Militký, J.: Kompendium statistického zpracování dat. Praha: Academia 2002. (CS)
Montgomery, D. C. - Renger, G.: Probability and Statistics. New York : John Wiley & Sons, Inc. 2010. (EN)
Ryan, T. P.: Modern Regression Methods. New York : John Wiley, 2004. (EN)
Recommended reading
Anděl, J.: Statistické metody. Praha : Matfyzpress, 2007. (CS)
Meloun, M. - Militký, J._: Statistické zpracování experimentálních dat. Praha : PLUS, 1994. (CS)
Meloun, M. - Militký, J._: Statistické zpracování experimentálních dat. Praha : PLUS, 1994. (CS)
Elearning
eLearning: currently opened course
Classification of course in study plans
Type of course unit
Lecture
20 hod., optionally
Teacher / Lecturer
Syllabus
Probability distributions for modeling of technical phenomena and processes.
Exploratory analysis for statistical data processing.
Random sample - model and properties.
Search methods of probability distributions.
Estimation of probability distributions parameters.
Testing statistical hypotheses of distributions.
Testing statistical hypotheses of parameters.
Introduction to ANOVA, nonparametric tests.
Elements of linear regression analysis.
Statistical software - properties and option use.
Exploratory analysis for statistical data processing.
Random sample - model and properties.
Search methods of probability distributions.
Estimation of probability distributions parameters.
Testing statistical hypotheses of distributions.
Testing statistical hypotheses of parameters.
Introduction to ANOVA, nonparametric tests.
Elements of linear regression analysis.
Statistical software - properties and option use.
Elearning
eLearning: currently opened course