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Lecturer(s)
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Smolka Petr, doc. Ing. Ph.D.
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Kutálková Eva, RNDr. Ph.D.
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Černeková Martina, Ing. Ph.D.
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Ponížil Petr, prof. RNDr. Ph.D.
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Kocourková Karolína, Ing. Ph.D.
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Elisek Petr, Ing. Ph.D.
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Zvoníček Tomáš, Ing.
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Course content
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1. Instrumental errors. 2. Distribution of measured quantity. 3. Estimating parametres of normal distribution. 4. Error estimations for indirect measurements. 5. Correlation and regression. 6. Statistical hypothesis testing. 7. Nonparametric tests.
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Learning activities and teaching methods
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Lecturing, Activating (Simulation, games, dramatization)
- Participation in classes
- 42 hours per semester
- Home preparation for classes
- 24 hours per semester
- Preparation for course credit
- 24 hours per semester
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| prerequisite |
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| Knowledge |
|---|
| Basic knowledge of mathematics. |
| Basic knowledge of mathematics. |
| learning outcomes |
|---|
| define the errors of measuring instruments |
| define the errors of measuring instruments |
| explain the distribution of data with respect to the normal distribution |
| explain the distribution of data with respect to the normal distribution |
| explain the calculation of the error of an indirectly measured quantity |
| explain the calculation of the error of an indirectly measured quantity |
| explain the principle of hypothesis testing |
| explain the principle of hypothesis testing |
| explain the principles of regression and correlation |
| explain the principles of regression and correlation |
| Skills |
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| estimate the errors of measuring instruments from the documentation |
| estimate the errors of measuring instruments from the documentation |
| calculate the quantiles of the normal distribution |
| calculate the quantiles of the normal distribution |
| calculate the error of an indirectly measured quantity |
| calculate the error of an indirectly measured quantity |
| test statistical hypothesis |
| test statistical hypothesis |
| calculate the parameters of the regression model |
| calculate the parameters of the regression model |
| teaching methods |
|---|
| Knowledge |
|---|
| Lecturing |
| Activating (Simulation, games, dramatization) |
| Activating (Simulation, games, dramatization) |
| Lecturing |
| Skills |
|---|
| Individual work of students |
| Individual work of students |
| Practice exercises |
| Practice exercises |
| assessment methods |
|---|
| Knowledge |
|---|
| Analysis of works made by the student (Technical products) |
| Anamnestic method |
| Grade (Using a grade system) |
| Grade (Using a grade system) |
| Analysis of works made by the student (Technical products) |
| Anamnestic method |
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Recommended literature
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ANDĚL, J. Základy matematické statistiky. MatfyzPress, 2011. ISBN 978-80-7378-162-0.
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BUDÍKOVÁ, M., KRÁLOVÁ, M., MAROŠ, B. Průvodce základními statistickými metodami. Grada, 2010. ISBN 978-80-247-3243-5.
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FREEDMAN, D., PISANI, R. Statistics, 4th ed.. W.W. Norton & Company, 2007. ISBN 978-0393929720.
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Jiří Neubauer, Marek Sedlačík, Oldřich Kříž. Základy statisticky. Aplikace v technických a ekonomických oborech. Praha, 2012. ISBN 978-80-247-4273-1.
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LEPŠ, J, ŠMILAUER, P. Biostatistika. EPISTEME, Praha, 2016. ISBN 978-80-7394-587-9.
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MELOUN, M., MILITKÝ, J. Kompendium statistického zpracování dat. Praha: Karolinum, 2012. ISBN 80-200-1396-2.
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