MAS02 Applied statistics II

Faculty of Science
Spring 2025
Extent and Intensity
2/0/0. 2 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
In-person direct teaching
Teacher(s)
RNDr. Marie Budíková, Dr. (lecturer)
Guaranteed by
doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science
Prerequisites
NOW( MAS02c Applied statistics II ) || NOW( MAS20c Applied statistics II )
MAS01
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 198 fields of study the course is directly associated with, display
Course objectives
The main goals of this course are: to master the methods of simple and multivariate correlation and regression analysis; to understand the basics of multifactor ANOVA and covariance analysis; introduction of cluster analysis, discrimination analysis, factor analysis.
Learning outcomes
After completing the course the student is able to:
evaluate dependencies between two or more variables;
model the dependencies between variables;
summarize the information contained in a large number of variables into a small number of new variables;
classify objects into groups based on quantitative variables.
Syllabus
  • Simple and multivariate correlation and regression analysis.
  • Multifactor ANOVA.
  • Cluster analyis.
  • Discriminant analysis.
  • Factor analysis.
  • Covariance analysis.
Literature
    recommended literature
  • HEBÁK, Petr. Statistické myšlení a nástroje analýzy dat. 2. vydání. Praha: Informatorium, 2015, 877 stran. ISBN 9788073331184. info
    not specified
  • MELOUN, Milan and Jiří MILITKÝ. Počítačová analýza vícerozměrných dat v příkladech. Praha: Academia, 2005. ISBN 80-200-1335-0. info
  • HENDL, Jan. Přehled statistických metod zpracování dat :analýza a metaanalýza dat. Vyd. 1. Praha: Portál, 2004, 583 s. ISBN 8071788201. info
Teaching methods
The weekly class schedule consists of 2 hour lecture and 1 hour of class exercises with special statistical software in computer classroom.
Assessment methods
The examination is partly written and partly oral. In the oral part, student presents his own statistical data analysis project. Colloquium has presentation part only, while credit is only written.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: every week.
General note: Předmět by si neměli zapisovat studenti matematických oborů.
Listed among pre-requisites of other courses
Teacher's information
The lessons are usually in Czech or in English as needed, and the relevant terminology is always given with English equivalents.

The target skills of the study include the ability to use the English language passively and actively in their own expertise and also in potential areas of application of mathematics.

Assessment in all cases may be in Czech and English, at the student's choice.

The course is also listed under the following terms Spring 2011 - only for the accreditation, Spring 2009, Spring 2010, Spring 2011, Spring 2012, spring 2012 - acreditation, Spring 2014, Autumn 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.
  • Enrolment Statistics (recent)
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