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Lecturer(s)
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Stoklasa Jan, Mgr. et Mgr. Ph.D.
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Course content
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Main topics of the course: a) Modelling in economics b) Ekonomic data c) Model validation d) Sensitivity analysis e) Data pre-processing f) Types of questionnaire data (types of data that can/cannot be obtained by surveys and questionnaires) g) Processin gof questionnaire data h) Construction of questionnaires i) Coding of answers j) Modelling of relationships among different types of variables, qualitative comparative analysis (QCA) k) QCA, specification and concretization of the rules, introduction to fuzzy models, fsQCA l) Possible sources of bias in questionnaires
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Learning activities and teaching methods
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Lecture, Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
- Homework for Teaching
- 30 hours per semester
- Attendace
- 25 hours per semester
- Semestral Work
- 20 hours per semester
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Learning outcomes
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The course introduces to student the basics of model building in economics, the types of data sets, their processing and analysis. The attention is paid mainly to data obtained through various types of surveys and questionnaires (and processing thereof), their specific features and differences from measured (measurable) data analysis. Guidelines for the design of questionnaires and possible shortcomings that can be encountered in this process are discussed. Finally the set-theoretic methodology and qualitative comparative analysis (with the possibility to reflect uncertainty using fuzzy sets) and the possibilities of their use in finding answers to research questions based on questionnaire data (potentially qualitative) are introduced and discussed.
Student will adopt basics of the processing of data obtained through surveys and questionnaires. He/she will be able to preprocess input data, and evaluate them using basic methods. Applying the qualitative comparative analysis methodology, the student will be able to assess the compatibility of an assumed relationship (pattern) with the available data. The student will be able to present the results of his/her analysis in the form of graphical outputs and draw relevant conclusions in the context of economic practice.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Student performance, Systematic Observation of Student, Seminar Work
Active work in seminars. Seminar paper on the processing of economic data applying the methods dicussed in the course (more detailed description in the Moodle page of the course) and its defence.
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Recommended literature
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RapidMiner Studio Manual.
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M. A. North. (2012). Data Mining for the Masses..
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M. Hofmann, R. Klinkenberg. (2016). RapidMiner: Data Mining Use Cases and Business Analytics Application..
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P. BERKA. (2003). Dobývání znalostí z databází.
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Stoklasa, J., Luuka, P., and Talášek, T. (2017). Set-theoretic methodology using fuzzy sets in rule extraction and validation - consistency and coverage revisited.
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Stoklasa, J., Talášek, T., Kubátová, J. and Seitlová, K. (2017). Likert Scales in Group Multiple-criteria Evaluation.
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