Course: Applied Statistics II

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Course title Applied Statistics II
Course code MUSKM/2AST2
Organizational form of instruction Lecture
Level of course Bachelor
Year of study 3
Semester Winter
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Homolka Lubor, Ing. Ph.D.
Course content
- Introduction to inferential statistics - Dependency analysis - an introduction - Testing one-sample tests (proportions, means) - Testing two-sample tests (proportions, means) - Contingency and association tables - ANOVA for one and two factors - Regression analysis - Correlation analysis - Non-parametric methods

Learning activities and teaching methods
Lecturing
  • Home preparation for classes - 58 hours per semester
  • Preparation for course credit - 23 hours per semester
  • Preparation for examination - 24 hours per semester
  • Participation in classes - 20 hours per semester
learning outcomes
Knowledge
Definuje rozdíl mezi deskriptivní a inferenční statistikou
Definuje rozdíl mezi deskriptivní a inferenční statistikou
Defines the difference between descriptive and inferential statistics
Defines the difference between descriptive and inferential statistics
Defines the difference between descriptive and inferential statistics.
Defines the difference between descriptive and inferential statistics.
Defines what a dependence between variables of a statistical population is
Formulate the procedure for evaluating statistical hypotheses
Formulate the procedure for evaluating statistical hypotheses
Defines what a dependence between variables of a statistical population is
Explains the difference between different tests of dependence
Explains the difference between different tests of dependence
Describes the principle of time series
Describes the principle of time series
Choose the right statistical method for evaluating formulated statistical hypotheses
Choose the right statistical method for evaluating formulated statistical hypotheses
Explains the difference between parametric and non-parametric tests
Explains the difference between parametric and non-parametric tests
Verify the statistical significance of formulated statistical hypotheses
Verify the statistical significance of formulated statistical hypotheses
Skills
Determines the degree of association in a contingency table
Determines the degree of association in a contingency table
Calculate tests related to a contingency table
Calculate tests related to a contingency table
Calculate the ANOVA test
Calculate the ANOVA test
Determines the significance of the interaction between categorical and metric variables (t-test, ANOVA)
Determines the significance of the interaction between categorical and metric variables (t-test, ANOVA)
Predict the dependent variable into the future in linear regression modeling
Predict the dependent variable into the future in linear regression modeling
Calculate regression and correlation analysis
Calculate regression and correlation analysis
Calculate the complete procedure for testing a statistical hypothesis
Decides whether or not to reject the null hypothesis based on critical value, p-value and confidence interval.
Decides whether or not to reject the null hypothesis based on critical value, p-value and confidence interval.
Calculate the complete procedure for testing a statistical hypothesis
Evaluates the result of a given statistical test
Evaluates the result of the given statistical test both statistically and factually.
Evaluates the result of a given statistical test
Evaluates the result of the given statistical test both statistically and factually.
teaching methods
Knowledge
Lecturing
Lecturing
assessment methods
Grade (Using a grade system)
Grade (Using a grade system)
Recommended literature
  • Budíková, M. a kol. Průvodce základními statistickými metodami. Praha: Grada, 2010. ISBN 978-80-247-3243-5.
  • Hendl, J. Přehlad statistických metod zpracování dat. Praha: Portál, 2004. ISBN 80-7178-820-1.
  • Klímek, Petr. Aplikovaná statistika : cvičení. Vyd. 2. uprav. Zlín : Univerzita Tomáše Bati, 2004. ISBN 807318253X.
  • Klímek, Petr. Aplikovaná statistika pro ekonomy. Vyd. 1. Zlín : Univerzita Tomáše Bati, 2003. ISBN 8073181487.
  • Klímek, Petr. Statistické metody pro ekonomy. Vyd. 1. Zlín : Univerzita Tomáše Bati ve Zlíni, 2001. ISBN 8073180138.
  • Pecáková, I. Statistika v terénních průzkumech. Praha: Professional Publishing, 2008. ISBN 978-80-86946-74-0.
  • Řezanková, H. Analýza dat z dotazníkových šetření. Praha: Professional Pzblishing, 2007. ISBN 978-80-86946-49-8.
  • Seger, Jan. Statistické metody v tržním hospodáoství. 1. vyd. Praha : Victoria Publishing, 1995. ISBN 8071870587.


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