Course: Advanced Statistical Methods

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Course title Advanced Statistical Methods
Course code KID/APSMP
Organizational form of instruction Lecture + Tutorial
Level of course Master
Year of study 1
Semester Summer
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Půlpán Zdeněk, prof. PhDr. RNDr. CSc.
  • Jahodová Berková Andrea, Mgr. Ph.D.
Course content
Random event and his probability, conditional probability. One-dimensional random variable. Two-dimensional and multiple random variable, function of random variable. Some important theoretical probability distributions. Limits theorems. Population and random sample, methods of descriptive statistics. Estimation theory. Testing hypotheses. Nonparametric methods. Linear regression. Correlation. Random number and its properties. Some methods of multivariate statistical analysis.

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Methods of individual activities, Projection
Learning outcomes
The main goal of discipline is to develop acquaintance concerning basic ideas of the probability theory and fundamental statistical methods used for data processing in technical and economical practice and to show potentialities of available statistical software.
Student knows commonly used statistical methods (including multivariates methods), comprehends principles on which are this methods based, is able to choose a right method to solve a concrete problem. Is able to use available statistical software.
Prerequisites
Theory of probability and statistics - bachelor degree

Assessment methods and criteria
Oral examination, Written examination

Given assignment confirms that a student has attended lessons to the extent required and fulfilled qualified requirements. Conditions for credit are: 1 seminary work. Form, contents and length of the exam are determined in accordance with Study and Examining Rules of University of Pardubice. The exam consists of two parts, a written test and a theoretical exam. Student passes successfully the written test as well as the theoretical part of the exam if he/she obtains at minimum 50% of possible points in each part.
Recommended literature
  • Arltová, M. Sbírka příkladů ze statistiky (A). Praha: VŠE, 1997.
  • Cassella, G. Berger, R. L. Statistical inference Duxbury. ISBN 0-534-24312-6.
  • Cyhelský, L., Hustopecký, J., Závodský, P.. Příklady k základům statistiky. Praha: SNTL, 1988. ISBN 04-317-88.
  • Cyhelský, Lubomír. Elementární statistická analýza. Praha: Management Press, 1996. ISBN 80-85943-18-2.
  • Hátle, J., Likeš, J. Základy počtu pravděpodobnosti a matematické statistiky. Praha: SNTL, 1974. ISBN 04-311-74.
  • Horálek, Vratislav. Základní statistické výpočty s podporou Microsoft Excel. Praha: Česká společnost pro jakost, 2001. ISBN 80-02-01427-8.
  • Hurt, J. Simulační metody. Praha: SPN.
  • Kolda, S. Úvod do počtu pravděpodobnosti a matematické statistiky. Univerzita Pardubice, 1998.
  • Kožíšek, J. Statistické tabulky a jejich použití. Praha: ČVUT, 1996.
  • Montgomery, D. C., Runger, G. C. Applied statistics and probability for engineers. John Willey & Sons, 2007. ISBN 0-471-74589-8.
  • Potocký, R. Zbierka úloh z pravděpodobnosti a matematickej štatistiky. Bratislava: Alfa, 1986. ISBN 63-570-86.
  • Spiegel, M. R., Schiller, J. J., Srinivasan, R. Propability and Statistics. McGraw-Hill, 2000. ISBN 0-07-135004-7.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Transport Engineering Study plan (Version): Applied Informatics in Transport (2016) Category: Informatics courses 1 Recommended year of study:1, Recommended semester: Summer