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Course detail

Statistical Analysis

Course unit code: FSI-9STA
Academic year: 2016/2017
Year of study: Not applicable.
Semester: winter
Number of ECTS credits:
Learning outcomes of the course unit:
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.
Mode of delivery:
Not applicable.
Prerequisites:
Rudiments of the probability theory and mathematical statistics.
Co-requisites:
Not applicable.
Recommended optional programme components:
Not applicable.
Course contents (annotation):
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.
Recommended or required reading:
Montgomery, D. C. - Renger, G.: Probability and Statistics. New York : John Wiley & Sons, Inc., 1996.
Anděl, J.: Statistické metody. Praha : Matfyzpress, 1993.
Meloun, M. - Militký, J._: Statistické zpracování experimentálních dat. Praha : PLUS, 1994.
Hahn, G. J. - Shapiro, S. S.: Statistical Models in Engineering. New York : John Wiley & Sons, Inc., 1994.
Lamoš, F. - Potocký, R.: Pravdepodobnosť a matematická štatistika. Bratislava : Alfa, 1989.
Dowdy, S. - Wearden, S.: Statistics for Research. New York : John Wiley & Sons, Inc., 1993.
Planned learning activities and teaching methods:
The course is taught through lectures explaining the basic principles and theory of the discipline.
Assesment methods and criteria linked to learning outcomes:
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.
Language of instruction:
Czech, English
Work placements:
Not applicable.
Course curriculum:
Not applicable.
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.
Specification of controlled education, way of implementation and compensation for absences:
Attendance at lectures is not compulsory, but is recommended.

Type of course unit:

Lecture: 20 hours, optionally
Teacher / Lecturer: doc. RNDr. Zdeněk Karpíšek, CSc.
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.

The study programmes with the given course