151-0353/02 – Data analysis for bachelor's thesis (ADBP)
Gurantor department | Department of Mathematical Methods in Economics | Credits | 4 |
Subject guarantor | doc. Ing. Václav Friedrich, Ph.D. | Subject version guarantor | doc. Ing. Václav Friedrich, Ph.D. |
Study level | undergraduate or graduate | Requirement | Compulsory |
Year | 3 | Semester | summer |
| | Study language | Czech |
Year of introduction | 2019/2020 | Year of cancellation | |
Intended for the faculties | EKF | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
The subject builds on the knowledge gained in Statistics for Economists (Statistics A).
In this course students will
- learn how to create, edit, analyse, interpret and present data files;
- learn how to create descriptive statistics, perform first and second level classification and become familiar with selected statistical tests suitable for use in undergraduate theses;
- learn the basics of academic writing (guidelines and standards, IMRaD, citations, basic typography).
Teaching methods
Lectures
Individual consultations
Tutorials
Other activities
Summary
The aim of the subject is to train students in the practical processing of statistical data. The choice of methods is oriented towards the processing of files obtained in marketing or other economic research, mainly for the needs of bachelor theses. The course is based on the knowledge of basic statistics (Statistics for Economists or Statistics A). The software used is MS Excel with the Real Statistics add-in.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
- active participation in exercises
- elaboration of ongoing tasks and their submission in electronic form
E-learning
- The subject is supported by an interactive course in LMS Moodle.
- Ongoing tasks are submitted and assessed via LMS Moodle.
Other requirements
- Knowledge of statistics at undergraduate level (e.g. Statistics A).
- Working with Microsoft Excel at a basic level.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Statistical research and presentation of results
2. Data file, data import and coding
3. Categorised data, frequency tables and graphs
4. From research objectives to hypothesis testing
5. Second level sorting, contingency table
6. Numerical data, characteristics and distribution plots
7. Comparative tests of variance and means
8. Analysis of variance ANOVA, multiple comparisons
9 Structure and formatting of scientific papers
10. Information sources, working with references and citations
11. Word processing and graphics on the computer
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction