Course: Cluster Analysis-Based Data Processing

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Course title Cluster Analysis-Based Data Processing
Course code USII/PZMSA
Organizational form of instruction Lecture + Tutorial
Level of course Bachelor
Year of study 2
Semester Winter
Number of ECTS credits 4
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Jonášová Hana, Ing. Ph.D.
Course content
Summary of statistical analysis key concepts. Summary of working with descriptive statistics in Excel. Key concepts of cluster analysis. Data standardisation and object normalisation. Resemblance relationships among objects. Non-resemblance cluster coefficients. Association coeficients. Hierarchical clustering methods. Aglomerate clustering method. Divisive methods of hierarchical clustering. Methods maintaining the set cluster number. Methods alternating the cluster number.

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Methods of individual activities, Laboratory work
Learning outcomes
This course is focused on the pre-processing of data and its further processing with hierarchical and non-hierarchical methods of cluster analysis and the possibilities of its application in data processing. Also included will be a summary of basic knowledge in the field of descriptive statistics and an introduction to data analysis tools offered by MS Excel.
Students will be able to select suitable processes and methods for solving given problems.
Prerequisites
Basic knowledge of statistics and skills in MS Excel utilization.

Assessment methods and criteria
Written examination, Home assignment evaluation, Discussion, Systematic monitoring

Assignment: successful elaboration of given tasks (provided in Stag) and elaboration of practical tasks on PC. Examination: Project. Detailed information will be provided during the first lecture and in Stag.
Recommended literature
  • Brož, M. Microsoft Excel pro manažery a ekonomy. Computer Press. ISBN 80-251-1307-8.
  • Kubanová J. Statistické metody pro ekonomickou a technickou praxi. Statis Bratislava, 2004. ISBN 80-85659-379.
  • Lukasová A. - Šarmanová J. Metody shlukové analýzy. 1985. ISBN ISBN 04-014.
  • Novák, Vilém. Fuzzy množiny a jejich aplikace. Praha: Státní nakladatelství technické literatury, 1990. ISBN 80-03-00325-3.
  • Řezanková, Hana. Shluková analýza dat. Praha: Professional Publishing, 2007. ISBN 978-80-86946-26-9.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Economics and Administration Study plan (Version): Information and Security Systems (2015) Category: Economy 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Informatics in Public Administration (2015) Category: Economy 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Informatics in Public Administration (2013) Category: Economy 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Information and Security Systems (2013) Category: Economy 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Informatics in Public Administration (2014) Category: Economy 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Economics and Administration Study plan (Version): Information and Security Systems (2014) Category: Economy 2 Recommended year of study:2, Recommended semester: Winter