Course: Statistical Data Analysis

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Course title Statistical Data Analysis
Course code KEM/SZD
Organizational form of instruction Lecture + Tutorial
Level of course Bachelor
Year of study not specified
Semester Winter and summer
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Gangur Mikuláš, Doc. RNDr. Ph.D.
  • Mičudová Kateřina, Ing. Ph.D.
  • Svoboda Milan, Ing. Mgr. Ph.D.
Course content
- Empirical research, hypothesis, planing and steps of research - Data sources for research, techniques of data gathering - Introduction to hypothesis testing, type 1 and type 2 errors, interpretation of results, test validity and reliability - Normality tests (chí-square, Liliefors test, graphical tests,), independence in contingency table, Chi-square test for independence. - One-sample tests (mean, variance, standard deviation) relation to interval estimation - Two-sample tests (means equity, variances equity, relative frequncies equity, paired two-sample test) - One factor ANOVA - Fundamentals of regression and correlation analysis.

Learning activities and teaching methods
Lecture with practical applications, Individual study, Self-study of literature, Practicum
  • Contact hours - 52 hours per semester
  • Preparation for comprehensive test (10-40) - 20 hours per semester
  • Undergraduate study programme term essay (20-40) - 20 hours per semester
  • Preparation for an examination (30-60) - 40 hours per semester
prerequisite
professional knowledge
apply basic knowledge of statistic (KEM/STA).
professional skills
determine characteristics of statistics file.
determine quantiles of random variable.
work in MS Excel.
general eligibility
N/A
N/A
N/A
N/A
learning outcomes
professional knowledge
methods of real data processing.
software for data processing.
interpretation and prezentation of data.
professional skills
assemble the research plan.
assemble questionaire for research.
make the suitbale random selection from population.
formulate research hypothesis and statisticaly evaluate them.
determkine distribution parameters using statistical test.
realize the test of mean equivalence for two or more samples.
decide about normality of data.
realize chi square in contingency table.
use statistical software for analyzing and statistical evaluation of data.
general eligibility
N/A
N/A
teaching methods
professional knowledge
Practicum
Self-study of literature
Individual study
Lecture with practical applications
professional skills
Practicum
Individual study
Discussion
Project-based instruction
general eligibility
Lecture supplemented with a discussion
Individual study
Task-based study method
assessment methods
professional knowledge
Written exam
Test
Seminar work
professional skills
Skills demonstration during practicum
Practical exam
Project
general eligibility
Practical exam
Project
Recommended literature
  • Hendl, J. Přehled statistických metod zpracování dat : analýza a metaanalýza dat. Praha: Portál, 2006. ISBN 80-7367-123-9.
  • Pecáková, I. Statistika v terénních průzkumech. Praha: Professional Publishing, 2011. ISBN 978-80-7431-039-3.
  • Řezánková, H. Analýza dat z dotazníkových šetření. Praha: Professional Publishing, 2011. ISBN 978-80-7431-062-1.
  • Řezánková, H. Analýza kategoriálních dat. Praha: Oeconomica, 2005. ISBN 80-245-0926-1.


Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester
Faculty of Economics Information Systems Management (2015) Economy 3 Winter
Faculty of Economics Information Systems Management (2017) Economy 3 Winter
Faculty of Economics Project Management Systems (2015) Economy 3 Winter
Faculty of Economics Business Economics and Management (2015) Economy 3 Winter
Faculty of Economics Business Economics and Management (2015) Economy 3 Winter
Faculty of Economics Retail Management (2015) Economy 3 Winter