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Lecturer(s)
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Course content
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1. Introduction to research and working with data - meaning of research, working with needs, basic types of research and research methods 2. Application and use of data - examples from practice, how and where data can be used everywhere, ethical aspects of working with data 3. Basics of methodology - preparing a research project, creating a session guide, research objectives, research limitations 4. Quantitative research methods - questionnaire survey, NPS, data coding, data visualization, data analysis, big data 5. Qualitative research methods - human-centered-design methods, concept testing, user testing, feeling maps 6. Secondary data - overview of secondary data sources, desk research, internal research and working with data 7. Secondary data - trend reports, panel data, company and industry analysis 8. Cognitive biases and how to work with them 9. Tools for working with data - visualization, interpretation, data tools, data analysis, PowerBI, Google Data Studio, etc. 10. Target group - recruitment, hypothesis and insight generation, segmentation and customer personas 11. Research agencies - how it works, team roles, research agency products, creating a brief for a research agency 12. Linking institutional objectives and data collection - what data and analysis are needed to monitor the achievement of the institution's or project's objectives 13. Data presentation - visualization, interpretation of teams, how to work with data within the organization
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Learning activities and teaching methods
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- Participation in classes
- 26 hours per semester
- Home preparation for classes
- 15 hours per semester
- Preparation for course credit
- 9 hours per semester
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| prerequisite |
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| Knowledge |
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| Prerequisities are not set. |
| Prerequisities are not set. |
| learning outcomes |
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| Understanding the importance of data and working with it |
| Understanding the importance of data and working with it |
| Understanding the basic methodology, how to work with and interpret data (quantitative vs. qualitative data) |
| Understanding the basic methodology, how to work with and interpret data (quantitative vs. qualitative data) |
| Basic knowledge and orientation in data evaluation and presentation tools |
| Basic knowledge and orientation in data evaluation and presentation tools |
| Moral aspects when working with data |
| Moral aspects when working with data |
| Conscious work with cognitive distortions |
| Conscious work with cognitive distortions |
| Skills |
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| Creating a research brief |
| Creating a research brief |
| Working with data within organizations or projects (links to strategic documents and organizational goals) |
| Working with data within organizations or projects (links to strategic documents and organizational goals) |
| Ability to set up data collection or secondary sources |
| Ability to set up data collection or secondary sources |
| Ability to make recommendations and decisions based on data |
| Ability to make recommendations and decisions based on data |
| Ability to implement and evaluate basic research methods (questionnaire, in-depth interview) |
| Ability to implement and evaluate basic research methods (questionnaire, in-depth interview) |
| teaching methods |
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| Knowledge |
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| Demonstration |
| Demonstration |
| Skills |
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| Practice exercises |
| Practice exercises |
| assessment methods |
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| Knowledge |
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| Preparation of a presentation |
| Preparation of a presentation |
| Analysis of the student's performance |
| Analysis of the student's performance |
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Recommended literature
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GEMIGNANI, Chris. Efektivní analýza a využití dat. Praha. 2015.
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HENDL, J., REMR, J. Metody výzkumu a evaluace. Praha: Portál, 2017. ISBN 978-80-262-1192-1.
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Kupka, Karel. Statistické řízení jakosti : interaktivní analýza a interpretace dat pro řízení jakosti a ekonomiku. Pardubice : TriloByte, 1997. ISBN 802381818X.
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