The experimental analysis on the performance of a proposed method is a crucial and necessary task to carry out in a research. This paper is focused on the statistical analysis of the results in the community of Genetic Based Machine Learning. Specifically, a non-parametric analysis can be performed by using the average results obtained for each data set as sample, which supposes in a simpler an...

Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS.

introduction: voxel based morphometry is a type of statistical parametric mapping that can be used to investigate the effect of diseases such as epilepsy, alzheimer's disease and parkinson's disease or other agent such as skills on brain structure (white matter, gray matter and cerebrospinal fluid). the aim of this study is evaluate the effectiveness of this method in detection of dif...

Cluster-based permutation tests are widely used in neuroscience studies for the analysis of high-dimensional electroencephalography (EEG) and event-related potential (ERP) data as it may address multiple comparison problem without reducing statistical power. However, classical cluster-based relies on parametric t-tests, whose assumptions not be verified case non-normality distribution alternati...

In this paper we propose and examine non–parametric statistical tests to define similarity and homogeneity measures for textures. The statistical tests are applied to the coefficients of images filtered by a multi–scale Gabor filter bank. We will demonstrate that these similarity measures are useful for both, texture based image retrieval and for unsupervised texture segmentation, and hence off...

The experimental analysis on the performance of a proposed method is a crucial and necessary task to carry out in a research. This paper is focused on the statistical analysis of the results in the field of genetics-based machine Learning. It presents a study involving a set of techniques which can be used for doing a rigorous comparison among algorithms, in terms of obtaining successful classi...

RATIONAL AND OBJECTIVES It is common to administer the same diagnostic test more than once to the same set of patients. The purpose of this study was to develop two statistical methods for estimating and comparing correlated receiver operating characteristic (ROC) curves for data derived from repeated diagnostic tests. MATERIAL AND METHODS Parametric and semiparametric transformation models w...