Course detail

Statistical Methods in Practice

FP-smpPAcad. year: 2019/2020

Introduction to modern methods of statistical processing of data and possibilities of using statistical software, for example, tasks associated with analysis of the survey.

Learning outcomes of the course unit

Ability to work with specialized software, knowledge bases analysis surveys, methods of ANOVA and cluster analysis

Prerequisites

Elements of probability theory and mathematical statistics .

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

ŘEZANKOVÁ, Hana. Analýza dat z dotazníkových šetření : (druhé vydání). 2. vyd. Praha : Professional Publishing, 2010. 217 s. ISBN 978-807-4310-195. (CS)
BUDÍKOVÁ, Marie; KRÁLOVÁ, Maria; MAROŠ, Bohumil. Průvodce základními statistickými metodami. 1. vyd. Praha : Grada, 2010. 272 s. ISBN 978-802-4732-435. (CS)
ŘEZANKOVÁ, Hana; HÚSEK, Dušan; SNÁŠEL, Václav. Shluková analýza dat. 2., rozš. vyd. Praha : Professional Publishing, 2009. 218 s. ISBN 978-808-6946-818. (CS)
ŘEZANKOVÁ, Hana; HÚSEK, Dušan; SNÁŠEL, Václav. Shluková analýza dat. 2., rozš. vyd. Praha : Professional Publishing, 2009. 218 s. ISBN 978-808-6946-818. (CS)
ŘEZANKOVÁ, Hana. Analýza dat z dotazníkových šetření : (druhé vydání). 2. vyd. Praha : Professional Publishing, 2010. 217 s. ISBN 978-807-4310-195. (CS)
BUDÍKOVÁ, Marie; KRÁLOVÁ, Maria; MAROŠ, Bohumil. Průvodce základními statistickými metodami. 1. vyd. Praha : Grada, 2010. 272 s. ISBN 978-802-4732-435. (CS)

Planned learning activities and teaching methods

The lecture combines theory with illustrative examples. The practical exercise is concerned on handling numerical tasks.

Assesment methods and criteria linked to learning outcomes

credit
Condition of obtaining credit is Poro development seminar work as the tutor. An excused absence of a student from seminars can be compensated for by submitting solution of alternate exercises.

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

1) Processing of data sets, statistical hypothesis testing
2) Designing a questionnaire
3) Analysis of dependence
4) Compare Files
5) Principles of clustering
6) Biologically inspired algorithms

Aims

Students will be able to design appropriate questionnaire and then evaluate the data. They will be able to process how to use commonly available Microsoft Excel, so statisticly specialized software.

Specification of controlled education, way of implementation and compensation for absences

Attendance at lectures is not compulsory but is recommended. Attendance at seminars is checked. Excused absence for student exercises can be replaced by a spare tasks.

Classification of course in study plans

  • Programme MGR Master's

    branch MGR-ŘEP , 1. year of study, summer semester, 2 credits, elective
    branch MGR-PFO , 1. year of study, summer semester, 2 credits, elective

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Exercise

13 hours, compulsory

Teacher / Lecturer

eLearning