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
Number of ECTS credits 5
Language of instruction Czech
Status of course unspecified
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.
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
  • Preparation for an examination (30-60) - 30 hours per semester
  • unspecified - 30 hours per semester
  • Contact hours - 52 hours per semester
  • Preparation for formative assessments (2-20) - 20 hours per semester
prerequisite
Knowledge
apply basic knowledge of statistic (KEM/STA)
Skills
determine characteristics of statistics file
determine quantiles of random variable
work in MS Excel
Competences
N/A
N/A
N/A
N/A
learning outcomes
Knowledge
process procedures of different types of real data
process data for software
interpret and present data
Skills
assemble the research plan
assemble questionaire for research
make the suitbale random selection from population
formulate research hypothesis and statisticaly evaluate them
determine 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
Competences
N/A
N/A
teaching methods
Knowledge
Practicum
Self-study of literature
Individual study
Interactive lecture
Task-based study method
E-learning
Skills
Practicum
Individual study
Project-based instruction
Task-based study method
Lecture
E-learning
Discussion
Competences
Lecture supplemented with a discussion
Individual study
Task-based study method
Practicum
E-learning
assessment methods
Knowledge
Written exam
Test
Seminar work
Practical exam
Skills
Skills demonstration during practicum
Practical exam
Project
Seminar work
Competences
Practical exam
Project
Recommended literature
  • Hendl, Jan. Přehled statistických metod zpracování dat : analýza a metaanalýza dat. Vyd. 2., opr. Praha : Portál, 2006. ISBN 80-7367-123-9.
  • Pecáková, Iva. Statistika v terénních průzkumech. 2., dopl. vyd. Praha : Professional Publishing, 2011. ISBN 978-80-7431-039-3.
  • Řezanková, Hana. Analýza dat z dotazníkových šetření. 3., aktualiz. vyd. Praha : Professional Publishing, 2011. ISBN 978-80-7431-062-1.
  • Řezanková, Hana. Analýza kategoriálních dat. Vyd. 1. Praha : Oeconomica, 2005. ISBN 80-245-0926-1.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester