Course Unit Code | 470-2404/01 |
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Number of ECTS Credits Allocated | 4 ECTS credits |
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Type of Course Unit * | Compulsory |
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Level of Course Unit * | First Cycle |
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Year of Study * | Third Year |
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Semester when the Course Unit is delivered | Winter Semester |
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Mode of Delivery | Face-to-face |
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Language of Instruction | Czech |
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Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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Name of Lecturer(s) | Personal ID | Name |
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| LIT40 | Ing. Martina Litschmannová, Ph.D. |
| VRT0020 | Mgr. Adéla Kondé |
Summary |
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Statistics is an important field of math that is used to analyze, interpret, and predict outcomes from data. This course will teach students the basic concepts used to describe data. With the knowledge gained in this course, students will be ready to undertake their first very own data analysis using the open source software R, which is rapidly becoming the leading programming language in statistics and data science. |
Learning Outcomes of the Course Unit |
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This subject is an introductory course of statistics. The aim of the course is to develop sufficient knowledge of statistical tools and procedures, understanding of the underlying theory on which the procedures are based, and facility in the application of statistical tools to enable the student to incorporate sound statistical methodology into other areas of his or her own work.
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Course Contents |
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1) Introduction to Probability Theory
2) Conditonal probability, Bayes Theorem
3) Discrete random variable
4) Discrete probability distributions
5) Continuous random variable
6) Continous probability distributions
7) Random Vector
8) Exploratory data analysis - qualitative variable and two qualitative variables
9) Exploratory data analysis - quantitative variable
10) Exploratory data analysis - two quantitative variables (independent variables vs. paired data)
11) Introduction to statistical induction, Introduction to estimation theory
12) Introduction to hypothesis testing (principle, hypothesis testing, statistical vs. practical significance, p-value)
13) One sample tests of mean and binomial test of proportion
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Recommended or Required Reading |
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Required Reading: |
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[1] CRAWLEY, Michael J. Statistics: an introduction using R. Chichester, West Sussex, England: J. Wiley, c2005. ISBN 978-0470022986
[2] StatSoft, Inc. (2013). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: http://www.statsoft.com
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[1] LITSCHMANNOVÁ, M. (2011), Úvod do statistiky, elektronická skripta, dostupné online z: http://mi21.vsb.cz/modul/uvod-do-statistiky
[2] CRAWLEY, Michael J. Statistics: an introduction using R. Chichester, West Sussex, England: J. Wiley, c2005. ISBN 978-0470022986 |
Recommended Reading: |
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[1] Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University. |
[1] PAVLÍK, T., DUŠEK, L. (2012): Biostatistika, Akademické nakladatelství CERM, ISBN 978-80-7204-782-6
[2] ZVÁROVÁ, J. (2016, 3. vydání): Základy statistiky pro biomedicínské obory I., Karolinum, ISBN 978-80-246-3416-6
[3] StatSoft, Inc. (2013). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: http://www.statsoft.com |
Planned learning activities and teaching methods |
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Lectures, Tutorials, Project work |
Assesment methods and criteria |
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Task Title | Task Type | Maximum Number of Points (Act. for Subtasks) | Minimum Number of Points for Task Passing |
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Credit and Examination | Credit and Examination | 100 (100) | 51 |
Credit | Credit | 40 (40) | 20 |
Homeworks | Other task type | 20 | 6 |
Homeworks | Other task type | 20 | 10 |
Examination | Examination | 60 | 30 |