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Last update: G_M (07.05.2014)
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Last update: G_M (07.05.2014)
Learn basic principles of probability theory and mathematical statistics. |
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Last update: RNDr. Jitka Zichová, Dr. (27.01.2016)
Jiří Anděl: Statistické metody. Matfyzpress, Praha, 2007.
Jiří Anděl: Matematika náhody. Matfyzpress, Praha, 2000.
Karel Zvára, Josef Štěpán: Pravděpodobnost a matematická statistika. Matfyzpress, Praha, 2002.
Karel Zvára: Biostatistika. Karolinum, Praha, 2008.
Karel Zvára: Základy statistiky v prostředí R. Karolinum, Praha, 2013. |
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Last update: G_M (07.05.2014)
Lecture. |
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Last update: T_KPMS (02.06.2016)
1) Introduction.
2) Descriptive statistics.
3) Basics of probability theory (random events, the definition of probability, conditional probability, independent events).
4) Random variable and its distribution. Characteristics of random variable. Examples of probability distributions.
5) Random vectors. Independent random variables, correlation.
6) Random sample. The law of large numbers. The central limit theorem.
7) Probabilistic and statistical approach in exploring real world. Estimates of the random variable characteristics.
8) Estimation theory. Hypothesis testing. Mathematical statistics as a basic tool for drawing conclusions from a scientific experimental work.
9) Selected statistical tests (one sample test, two sample test, paired test, some nonparametric tests, independence testing in contingency table.).
10) Linear regression model. |