Course objectives:
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The aim of this course is to introduce basic ideas of probability and statistical analysis. The course aims at introducing the students to descriptive statistics, graphical presentation of statistical data, to apply statistical analysis using statistical software.
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Requirements on student
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Final examination consists of written test (70%) and oral examination (30%).
Knowledge and abilities assessed: All assessment tasks will assess the learning outcomes, especially, the ability to provide logical and coherent proofs of results, procedures and specific problems related to statistic inference.
Assessment criteria: The main criteria for marking will be clear and logical formulation of solution methods and correctness of interpretation of obtained results.
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Content
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Course programme: 1. Introductory statistics. 2. Basic descriptive statistics in Excel. 3. Graphical presentation of statistical data. 4. Probability and probability models 5. List of probability distributions 6. Estimation of Parameters 7. Statistical test of Significance 8. Parametric and nonparametric methods 9. Presenting and summarising the multivariate data. 10. Correlation and regression.
Programme of seminars: 1. Survey statistical software. 2. Basic descriptive statistics in Excel. 3. Graphical presentation of statistical data. 4. Graphical presentation of statistical data. 5. List of probability distributions. 6. Point estimation and interval. 7. Statistical hypothesis testing. Parametric methods. 8. Statistical hypothesis testing. Nonparametric methods. 9. Contingence tables. 10. Correlation and regression.
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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Preparation for formative assessments (2-20)
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20
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Preparation for an examination (30-60)
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20
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Contact hours
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40
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Total
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80
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
Students should have practical experience with office suite applications. |
Popsat a vysvětlit základní principy statistické inference (principy bodových odhadů, intervalových odhadů a principy testování statistických hypotéz) |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
Ovládat na uživatelské úrovni program Excel. |
Použít statistické metody a postupy pro vyhodnocování dat (s i bez použití počítače). |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
mgr. studium: kriticky přistupuje ke zdrojům informací, informace tvořivě zpracovává a využívá při svém studiu a praxi |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
Learning outcomes:
On completion of this module the student will be able to:
- describe the statistical SW applicable for statistical data processing;
- review fitness SW for choice statistical problems;
- illustrate using SW on simple examples;
- use select SW for statistical data processing;
- apply statistical principles on real problems and suggest their solving in SW;
- interpret the statistic results. |
Skills - skills resulting from the course: |
- znát statistické funkce v sw Excel (případně v dalších statisticky orientovaných softwarech)
- aplikovat teoretické poznatky z oblasti pravděpodobnosti v SW Excel (případně v dalších statisticky orientovaných softwarech)
- využívat znalosti základních statistických metod a postupů pro analýzu dat v sw Ecxel (případně v dalších statisticky orientovaných softwarech)
- aplikovat statistické principy na vybrané reálné problémy a navrhnout jejich řešení ve zvoleném SW prostředí |
Competences - competences resulting from the course: |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Combined exam |
Seminar work |
Skills - skills achieved by taking this course are verified by the following means: |
Combined exam |
Seminar work |
Competences - competence achieved by taking this course are verified by the following means: |
Combined exam |
Seminar work |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Individual study |
Interactive lecture |
Skills - the following training methods are used to achieve the required skills: |
Interactive lecture |
Individual study |
Competences - the following training methods are used to achieve the required competences: |
Individual study |
Interactive lecture |
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