The lecture is devided into three parts. The first part deals with basics of probability theory and statistic processing of experimental data. The second part is about statistical test, while the main aim of the lecture if focused into the third part, which corresponds to regression analysis. The lecture is mainly focused on aplication of such statistical methods to real chemical problems, mainly in seminars that complete the lectures. 1. Random variable - experimental errors, stochastic event, probability, continuous distribution, discrete distribution, general and central moments, covariation and correlation coeficient, random vector, covariance matrix. 2. General terms of statistics - statistical and random variable, point estimates, interval estimates 3. Exploration analyzes - order statistics, histograms, quantile diagram, variation diagram, box diagram, half-sum diagram, symmentry diagram, Q-Q diagram, verification of hypotheses 4. Testing of statistical hypotheses - one-sample Student's t-test, two-samples Student's t-test, paired Student's t-test, outlier tests, F-test, testing in EXCEL, non-parametric tests 5. Analyzes of variation - ANOVA - single factor ANOVA, ANOVA for multiple factors (with/without interactions) 6. Correlation - correlation coefficient, pivot table 7. Linear regression 8. Non-linear regression 9. Basic fragments of mathematics
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Pytela O.. (1993). Chemometrie pro organické chemiky. UPCE Pardubice.
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Hendl, J. (2004). Přehled statistických metod zpracování dat: analýza a metaanalýza dat. Praha: Portál.
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Meloun, M., Militký, J. (1998). Statistické zpracování experimentálních dat. East Publishing Praha.
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Otyepka, M., Banáš, P., Otyepková, E. (2013). Základy zpracování dat. VUP Olomouc.
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