Course: Statistical and Mathematical Methods of Management

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Course title Statistical and Mathematical Methods of Management
Course code KAP/SMM-D
Organizational form of instruction Lecture + Seminary
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 15
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Course availability The course is available to visiting students
Lecturer(s)
  • Picek Jan, prof. RNDr. CSc.
  • Skalská Hana, prof. RNDr. CSc.
  • Linda Bohdan, doc. RNDr. CSc.
  • Kubanová Jana, doc. PaedDr. CSc.
Course content
Probability and statistics: Probability distrubution models and their application in inference, analysis of cathegorical data, parametric and non-parametric hypothesis testing, factorial experiments. Multivariate methods: regression models and inference in linear regression, discriminant function analysis or other types of predictive models (logistic regression, decision trees, etc.), cluster analysis. Decision support systems: modelling, causality, sample survey problems and generalization, data and their usage in decision making, software for data analysis, data visualization.

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing)
  • Class attendance - 560 hours per semester
Learning outcomes
Advanced methods of inductive statistics. Students should develop skills and knowledge specific for statistical considerations supporting a comprehensive approach to solutions of real problems.
Students obtain knowledge in given course in accordance with requirements and course programme.
Prerequisites
Knowledge in given course in accordance with requirements and course programme.

Assessment methods and criteria
Combined examination, Oral exam

Elaboration of a project as instructed by a teacher. The defense of the project is part of the exam.
Recommended literature
  • ANDERSON, T. W. An Introduction to Multivariate Statistical Analysis. 2003. ISBN 978-0-471-36091-9.
  • Dalgaard, P. Introductory Statistics with R. 2008. ISBN 978-0-387-79053-4.
  • Hebák, P. a kol. Vícerozměrné statistické metody. Informatorium, Praha, 2007.
  • HEBÁK, P. et al. Vícerozměrné statistické metody (3). Informatorium.. Praha, 2005. ISBN 80-7333-039-3.
  • Hebák, P., Hustopecký, J., Malá, I. Vícerozměrné statistické metody (2). Informatorium, Praha, 2005. ISBN 80-7333-036-9.
  • Isson, J. a Harriot, J. Win with Advanced Business Analytics: Creating Business Value from Data.
  • JUREČKOVÁ, J., P. K. SEN a J. PICEK. Methodological Tools in Robust and Nonparametric Statistics. 2013. ISBN 978-1-4398-4068-9.
  • KING, R.S. Cluster Analysis and Data Mining: An Introduction. 2015. ISBN 978-1938549-38-0.
  • Kubanová, J. Statistické metody pro ekonomickou a technickou praxi.
  • Linda, B. Pravděpodobnost.
  • REIMANN C., P. FILZMOSER, R. GARRETT a R. DUTTER. Statistical Data Analysis Explained. 2008. ISBN 978-0-470-98581-6.
  • ŘEZANKOVÁ, H. Analýza dat z dotazníkových šetření. 2. vyd. Praha: Professional Publishing, 2010.
  • S. COLES. An Introduction to Statistical Modeling of Extreme Values. 2001. ISBN 978-1-85233-459-8.
  • Skalská, H., Stránský, P. Základy biostatistiky. Karolinum, Praha, 2007.
  • Wonnacott, T.H., Wonnacott, R.J. Introductory Statistics for Business and Economics. New York : John Wiley & Sons, 1990. ISBN 0-471-61517-X.
  • Zhao, Z. R and Data Mining: Examples and Case Studies. 2013. ISBN 978-0-12-396963-7.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Economics Study plan (Version): Managerial Informatics (2014) Category: Economy 2 Recommended year of study:2, Recommended semester: Summer
Faculty: Faculty of Economics Study plan (Version): Managerial Informatics (2014) Category: Economy 2 Recommended year of study:2, Recommended semester: Summer