Course: Experiment Evaluation II

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Course title Experiment Evaluation II
Course code TUFMI/TE8ZE
Organizational form of instruction Lecture
Level of course Master
Year of study not specified
Semester Summer
Number of ECTS credits 2
Language of instruction English
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Kutálková Eva, RNDr. Ph.D.
  • Ponížil Petr, prof. RNDr. Ph.D.
Course content
- Normal distribution, normality testing. - Statistical hypothesis testing. - Linear regression. - Nonlinear regression. - Analysis of variance (ANOVA). - Nonparametric methods. - Experiment planning.

Learning activities and teaching methods
Monologic (Exposition, lecture, briefing), Dialogic (Discussion, conversation, brainstorming), Practice exercises
  • Preparation for course credit - 60 hours per semester
learning outcomes
Knowledge
test statistical hypothesis
test statistical hypothesis
explain linear regression models
explain linear regression models
explain non-linear regression models
explain non-linear regression models
define one and two factor ANOVA
define one and two factor ANOVA
design appropriate non-parametric tests
design appropriate non-parametric tests
Skills
use basic and more advanced statistical methods in the processing of experimental data
use basic and more advanced statistical methods in the processing of experimental data
test statistical hypotheses
test statistical hypotheses
calculate the parameters of the regression models and test them
calculate the parameters of the regression models and test them
analyze one and two factor ANOVA
analyze one and two factor ANOVA
test the data using non-parametric tests
test the data using non-parametric tests
teaching methods
Knowledge
Dialogic (Discussion, conversation, brainstorming)
Dialogic (Discussion, conversation, brainstorming)
Monologic (Exposition, lecture, briefing)
Monologic (Exposition, lecture, briefing)
Skills
Practice exercises
Practice exercises
Individual work of students
Individual work of students
assessment methods
Knowledge
Grade (Using a grade system)
Grade (Using a grade system)
Didactic test
Didactic test
Recommended literature
  • ANDĚL, J. Základy matematické statistiky. Praha: MatfyzPress, 2011. ISBN 9788073781620.
  • BUDÍKOVÁ, M., KRÁLOVÁ, M., MAROŠ, B. Průvodce základními statistickými metodami. Praha: Grada, 2010. ISBN 978-80-247-3243-5.
  • FREEDMAN, D., PISANI, R. Statistics, 4th ed.. W.W. Norton & Company, 2007. ISBN 978-0393929720.
  • LEPŠ, J., ŠMILAUER, P. Biostatistika. Praha: EPISTEME, 2016. ISBN 978-80-7394-587-9.
  • McCLAVE, J.T., SINCICH, T.T. Statistics. Cambridge: Pearson Publishing, 2012. ISBN 0321755936.
  • MELOUN, M. Statistické zpracování experimentálních dat. Praha: Plus, 1994. ISBN 80-85297-56-6.
  • NEUBAUER, J., SEDLAČÍK, M., KŘÍŽ, O. Základy statistiky. Aplikace v technických a ekonomických oborech. 2. roz. vyd.. Praha: Grada, 2016. ISBN 978-80-247-5786-5.
  • WITTE, R.S., WITTE, J.S. Statistics. New York, 2009. ISBN 978-0470392225.


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