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Lecturer(s)
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Course content
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Basic statistical terminology. Stages of statistical survey. Theory of errors. Random event. Probability. General population and sampling population. The rules of distribution one-dimensional random variable. Distribution of discrete random variable. Distribution of continuous random variable General concepts of point and interval estimation. Statistical hypothesis testing - parametric tests. Nonparametric tests. Exploratory analysis of one dimensional data. Analysis of variance. Dependencies of random variables - functional, regression, correlation, tightness of dependence. Simple linear regression and multiple linear regressions. Design of Experiments. Principles of statistical quality control.
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Learning activities and teaching methods
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unspecified, Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Skills training, Graphic and art activities
- Preparation of a presentation (report)
- 4 hours per semester
- Term paper
- 25 hours per semester
- Home preparation for classes
- 12 hours per semester
- Preparation for an exam
- 40 hours per semester
- Preparation for a partial test
- 12 hours per semester
- Data/material collection
- 5 hours per semester
- Participation in classes
- 52 hours per semester
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Learning outcomes
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The aim of this subject is to provide students with theoretical and mathematical principles needful for orientation in commonly used statistical characteristics. Emphasis is mainly put on practical skills, i.e. on encompassment of data processing using Excel and on subsequent interpretation and presentation of results.
Student is after fulfillment of this subject able to orientate himself properly in basic statistical characteristics and to use appropriate basic statistical methods of data processing mainly using Excel. He is competent to design and to carry out appropriate ways to get data, their processing, analyze, interpretation and presentation of results considering practice in chemical enterprise or laboratory. Fulfillment of this subject is fundamental prerequisite for study of consequential subject Economic
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Prerequisites
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Knowledge in mathematics on high school level is needed for study of the subject.
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Assessment methods and criteria
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Oral examination, Written examination, Home assignment evaluation, Student performance assessment, Discussion
Exam has two parts - written with computer and oral one. Level of acquired knowledge, approaches, as well as application skills, are examined. The knowledge are screened during semester through examination paper done on computer and its results are counted in total classification.
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Recommended literature
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Budíková M., Králová M., Maroš B. Průvodce základními statistickými metodami. Grada Publishing, a.s., 2011.
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HENDL J. Přehled statistických metod zpracování dat, Portál, s.r.o. Praha, 2004..
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Kožíšek J., Stieberová B. Statistika v příkladech, Verlag Dashofer, 2012.
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Marek L. a kol. Statistika v příkladech. Professional Publishing, Praha, 2013.
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Meloun M., Militký J. Kompendium statistického zpracování dat. Karolinum Praha, 3. vydání 2012.
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Montgomery, Douglas C. Applied statistics and probability for engineers. Hoboken: John Wiley & Sons, 2007. ISBN 978-0-471-74589-1.
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SOUČEK E. Základy pravděpodobnosti a statistiky. Skripta Univerzita Pardubice, 2004, ISBN80-7194-611-7..
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Vlčková V., Machač O., Paták M. Aplikovaná statistika, Skripta na CD, Univerzita Pardubice 2013,.
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Vlčková V. Studijní materiály k předmětu Aplikovaná statistika - k dispozici na: http://stag.upce.cz/.
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