This paper examines the problem of simultaneously testing many independent multiple hypotheses within the minimum encoding framework. We introduce an efficient coding scheme for nominating the accepted hypotheses in addition to compressing the data given these hypotheses. This formulation reveals an interesting connection between multiple hypothesis testing and mixture modelling with the class ...

Often, biogeography is applied only as a narrative addition to phylogenetic studies and lacks scientific rigour. However, if research questions are framed as hypotheses, biogeographical scenarios become testable. In this review, we explain some problems with narrative biogeography and show how the use of explicit hypotheses is changing understanding of how organisms came to be distributed as th...

This paper reviews important concepts and methods that are useful for hypothesis testing. First, we discuss the Neyman-Pearson framework. Various approaches to optimality are presented, including finite-sample and large-sample optimality. Then, some of the most important methods are summarized, as well as resampling methodology which is useful to set critical values. Finally, we consider the pr...

In most biomedical research, investigators hypothesize about the relationships of various factors, collect data to test those relationships, and try to draw conclusions about those relationships from the data collected. In many cases, investigators test relationships by comparing the average level of a factor between 2 groups or between 1 group and a standard reference. This framework is as tru...

The power of multiple testing procedures can be increased by using weighted p-values (Genovese, Roeder and Wasserman 2005). We derive the optimal weights and we show that the power is remarkably robust to misspecification of these weights. We consider two methods for choosing weights in practice. The first, external weighting, is based on prior information. The second, estimated weighting, uses...

A collaborative distributed binary decision problem is considered. Two statisticians are required to declare the correct probability measure of two jointly distributed memoryless process, denoted by X = (X1, . . . , Xn) and Y n = (Y1, . . . , Yn), out of two possible probability measures on finite alphabets, namely PXY and PX̄Ȳ . The marginal samples given by X and Y n are assumed to be availabl...

We initiate the study of differentially private hypothesis testing in the local-model, under both the standard (symmetric) randomized-response mechanism [War65, KLN08] and the newer (non-symmetric) mechanisms [BS15, BNST17]. First, we study the general framework of mapping each user’s type into a signal and show that the problem of finding the maximumlikelihood distribution over the signals is ...

T he process of drawing conclusions about an entire population on the basis of the information contained in a random sample drawn from that population is known as statistical inference. Methods of statistical inference fall into 2 general categories: estimation and hypothesis testing. With estimation, our goal is to describe or estimate some characteristic of a population of interest, such as t...

companies' continuity, because all companies have some relations with the society;Therefore, the society provides long-term survival of the company.In this way, companies in addition to economic responsibility, must take responsibilityof social issues. Therefore, with respect to corporate social responsibility andits revelations, the current paper examines the relationship between social respon...

Falsification may demarcate science from non-science as the rational way to test the truth of hypotheses. But experimental evidence from studies of reasoning shows that people often find falsification difficult. We suggest that domain expertise may facilitate falsification. We consider new experimental data about chess experts’ hypothesis testing. The results show that chess masters were readil...