Choosing appropriate statistical tests is crucial but deciding which to use can be challenging. Different suit different types of data and research questions, so it important choose the right one. Knowing how select an test lead more accurate results. Invalid results misleading conclusions may drawn from a study if incorrect used. Therefore, avoid these essential understand nature data, questio...

Parametric statistical methods are traditionally employed in functional magnetic resonance imaging (fMRI) for identifying areas in the brain that are active with a certain degree of statistical significance. These parametric methods, however, have two major drawbacks. First, it is assumed that the observed data are Gaussian distributed and independent; assumptions that generally are not valid f...

In this work, we get focused on the use of statistical techniques for behavior analysis of Artificial Neural Networks in the task of classification. A study of the non-parametric tests use is presented, using some well-known models of neural networks. The results show the need of using non-parametric statistic, because the Artificial Neural Networks used do not verify the hypothesis required fo...

BACKGROUND AND OBJECTIVES Statistical analysis is necessary for adequate evaluation of the original article by the reader allowing him/her to better visualize and comprehend the results. The objective of the present study was to determine the frequency of the adequate use of statistical tests in original articles published in the Revista Brasileira de Anestesiologia from January 2008 to Decembe...

Listening tests and Mean Opinion Scores (MOS) are the most commonly used techniques for the evaluation of speech synthesis quality and naturalness. These are invaluable in the assessment of subjective qualities of machine generated stimuli. However, there are a number of challenges in understanding the MOS scores that come out of listening tests. Primarily, we advocate for the use of non-parame...

In this paper, we focus on the experimental analysis on the performance in cluster analysis with the use of nonparametric tests on the clustering task. Particularly, we have studied whether the sample of results from multiple trials obtained by conventional clustering algorithms checks the necessary conditions for being analyzed through parametrical tests. The study is conducted by considering ...

This chapter reviews statistical testing involving phylogenies. We present both the classical framework with the use of sampling distributions involving the bootstrap and permutation tests and the Bayesian approach using posterior distributions. We give some examples of direct tests for deciding whether the data support a given tree or trees that share a particular property, comparative analyse...