| Abstract [eng] |
Statistical Hypothesis Testing. The work consists of two parts: in the first part two simple hypotheses were tested and a statistical criterion which should meet the following specifications was applied: 1 – the probability of type I error was defined and 2 - the probability of type II error was minimized. The asymptote formula of behaviour of the probability of type II error was obtained in the work when the n number of the data was approaching infinity. In the second part of the work three simple hypotheses were tested. It has been explored how the minimum error probability of all available errors, i.e., the error probability of the optimal minimax criterion, performed when the n number of the data was indefinitely increasing. The error probability analysed in the first part of the work was asymptotically decreasing in proportion to the Kulbak distance while the corresponding error probability analysed in the second part of the work was respectively decreasing in proportion to the Censov distance. Moreover, the properties of the distances mentioned above were described in the theoretical part of the work. The work concludes with choosing a polynomial distribution as an example which has demonstrated how the two asymptote formulas of the two results were obtained and how the asymptotic behaviour of testing of respective hypotheses looked like. |
