drop plate technique has a priority and preference compared with the spread plate procedure, because of less time, quantity of media, effort requirement, little incubator space, and less labor intensive. the objective of this research was to compare the accuracy and fidelity of drop plate method vs. spread plate method by parametric and nonparametric statistical tests. for bacterial enumeration...

This paper presents new biostatistical methods for the analysis of microbiome data based on a fully parametric approach using all the data. The Dirichlet-multinomial distribution allows the analyst to calculate power and sample sizes for experimental design, perform tests of hypotheses (e.g., compare microbiomes across groups), and to estimate parameters describing microbiome properties. The us...

Dedicated to the 70th birthday of Johann Pfanzagl Summary. Along the lines of Pfanzagl's work the testing theory for the non-parametric null hypothesis of symmetry (including matched pairs) is developed. The testing problem is typically given by a skew symmetric statistical functional which seems to be adequate for the nonparametric world. Under mild regularity assumptions asymptotically maximi...

evaluation of river discharges trends is very important for water resources management and design of irrigation and drainage networks. in this research, annual, seasonal and monthly trends of maroon river discharge were evaluated using the mann-kendall and sen’s slope estimator non-parametric tests and the regression analysis parametric test. for this purpose, river discharge data from five h...

We study partitions of the symmetric group which have desirable geometric properties. The statistical tests defined by such partitions involve counting all permutations in the equivalence classes. These permutations are the linear extensions of partially ordered sets specified by the data. Our methods refine rank tests of non-parametric statistics, such as the sign test and the runs test, and a...

Although many parametric statistical tests are considered to be robust, as recently shown in Methodologist's Corner, it still pays to be circumspect about the assumptions underlying statistical tests. In this paper I show that robustness mainly refers to α, the type-I error. If the underlying distribution of data is ignored there can be a major penalty in terms of the β, the type-II error, repr...