Common using of parametric tests to elaborate research results is limited by predetermined assumptions (variable measurability, normality of its distribution, homogeneity of database etc), which must be fulfilled. Otherwise, the conclusions obtained by calculating using a parametric test will not be quite correct. Parametric tests are useless also in the case of the quality data and the data of...

A novel method for color image retrieval, based on statistical non-parametric tests such as twosample Wald Test for equality of variance and Man-Whitney U test, is proposed in this paper. The proposed method tests the deviation, i.e. distance in terms of variance between the query and target images; if the images pass the test, then it is proceeded to test the spectrum of energy, i.e. distance ...

In this paper we focus on latent class analysis of a large data set. The data deal with antisocial behaviour which is measured by 24 dichotomous variables. Latent class analysis of such huge data sets is unusual. One of the reasons is that latent class analysis defines models for contingency tables, so, if there is a set of k dichotomous items, then a table of 2 cells is modeled. It will be cle...

A novel method for color image retrieval based on statistical non-parametric tests such as two-sample Wald Test for equality of variance and Man-Whitney U test is proposed in this paper. The proposed method tests the deviation, i.e. distance in terms of variance between the query and target images; if the images pass the test, then it is proceeded to test the spectrum of energy, i.e. distance b...

This paper presents an investigation of the separate perceptual degradations introduced by the modelling of source and filter features in statistical parametric speech synthesis. This is achieved using stimuli in which various permutations of natural, vocoded and modelled source and filter are combined, optionally with the addition of filter modifications (e.g. global variance or modulation spe...

Statistical parametric mapping (SPM) analysis of fMRI data requires specifying correctly the temporal and spatial noise covariance structure. This is a difficult if not impossible task. When these assumptions are not satisfied, statistical inference can be invalid or inefficient. Permutation tests are free of strong assumptions on the distribution of signal noise. We propose permutation tests o...

This chapter is written for analysts and researchers who may use Data Envelopment Analysis (DEA) to statistically evaluate hypotheses about characteristics of production correspondences and factors affecting productivity. Contrary to some characterizations, it is shown that DEA is a full-fledged statistical methodology, based on the characterization of DMU efficiency as a stochastic variable. T...