Plan : 1- Introduction. 2- Choix entre deux probabilités. 2.1 Définition des experts. p. 10 2.2 Fonctions de test simples. p. 13 2.3 Ensemble des experts. p. 16 2.4 Votes des experts. p. 19 2.5 Vote pondéré. p. 23 3- Règles de décision de Bol'shev. 3.1 Définitions et propriétés. p. 25 3.2 Votes des experts et règles de Bol'shev. p. 31 4- Choix entre deux hypothèses stables. 4.1 Définitions. p. 37 4.2 Ensemble des experts. p. 41 4.3 Votes des experts. p. 56 5- Modèles à rapport de vraisemblance monotone. 5.1 Hypothèses unilatérales. p. 66 5.2 Votes compatibles sur une famille d'hypothèses unilatérales. p. 78 5.3 Hypothèses bilatérales. p. 106 5.4 Exemples. p. 122 6 - Hypothèses stables et paramètres fantômes. 6.1 Introduction. p. 131 6.2 Modèles exponentiels. p. 137In this study, we introduce a new approach to statistical decision theory. Without using a loss function, we select good decision rules to choice between two hypotheses. We call them "experts". They are globally unbiased but also conditionally unbiased on a family of events. We do not try to define the best expert. We define a probability distribution on the space of "experts". The measure of evidence for a hypothesis is the inductive probability of experts that decide this hypothesis, we call this measure: a "vote". We compare this point of view with the p-values. For some family of hypotheses, the "votes" can define a probability on the space of parameters. We compare these results with the Bayes posterior distributions. We study in detail real-parameter families of distributions with monotone likelihood ratio and multiparameter exponential families
