False discovery rateIn statistics, the false discovery rate (FDR) is a method of conceptualizing the rate of type I errors in null hypothesis testing when conducting multiple comparisons. FDR-controlling procedures are designed to control the FDR, which is the expected proportion of "discoveries" (rejected null hypotheses) that are false (incorrect rejections of the null). Equivalently, the FDR is the expected ratio of the number of false positive classifications (false discoveries) to the total number of positive classifications (rejections of the null).
Lobe (cerveau)thumb|right|Les lobes externes du cerveau humain. Sont aussi dessinés le cervelet en bleu et le tronc cérébral en noir qui sont des structures nerveuses distinctes du cerveau proprement dit. thumb|right|150px| Vue en 3D des lobes thumb|right| Vue en 3D des lobes externes du cerveau : frontal (rouge), pariétal (orange), temporal (vert), et occipital (jaune).Sont également représentés le cervelet (bleu) et le tronc cérébral (noir). En anatomie, chacun des deux hémisphères du cerveau est divisée en plusieurs lobes dont quatre sont dits externes et deux sont dits internes.
Statistical theoryThe theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches. Within a given approach, statistical theory gives ways of comparing statistical procedures; it can find a best possible procedure within a given context for given statistical problems, or can provide guidance on the choice between alternative procedures.
Climate as complex networksThe field of complex networks has emerged as an important area of science to generate novel insights into nature of complex systems The application of network theory to climate science is a young and emerging field. To identify and analyze patterns in global climate, scientists model climate data as complex networks. Unlike most real-world networks where nodes and edges are well defined, in climate networks, nodes are identified as the sites in a spatial grid of the underlying global climate data set, which can be represented at various resolutions.
Système de référence en anatomieUn système de référence en anatomie désigne la terminologie utilisée pour se repérer de façon précise dans la structure anatomique d'un organisme, humain ou non. Un système de référence anatomique repose sur un ensemble de plans et d'axes définis par rapport à la position standard de l'organisme décrit. Par exemple, on utilise cette terminologie pour indiquer l'orientation des coupes histologiques ou des vues utilisées dans les schémas et images en ou en biologie humaine à partir de la position anatomique (dite de Poirier), c'est-à-dire lorsque le sujet est debout face à l'observateur.
Small-world networkA small-world network is a mathematical graph in which most nodes are not neighbors of one another, but the neighbors of any given node are likely to be neighbors of each other. Due to this, most neighboring nodes can be reached from every other node by a small number of hops or steps. Specifically, a small-world network is defined to be a network where the typical distance L between two randomly chosen nodes (the number of steps required) grows proportionally to the logarithm of the number of nodes N in the network, that is: while the global clustering coefficient is not small.
Sample maximum and minimumIn statistics, the sample maximum and sample minimum, also called the largest observation and smallest observation, are the values of the greatest and least elements of a sample. They are basic summary statistics, used in descriptive statistics such as the five-number summary and Bowley's seven-figure summary and the associated box plot. The minimum and the maximum value are the first and last order statistics (often denoted X(1) and X(n) respectively, for a sample size of n).
False positive rateIn statistics, when performing multiple comparisons, a false positive ratio (also known as fall-out or false alarm ratio) is the probability of falsely rejecting the null hypothesis for a particular test. The false positive rate is calculated as the ratio between the number of negative events wrongly categorized as positive (false positives) and the total number of actual negative events (regardless of classification). The false positive rate (or "false alarm rate") usually refers to the expectancy of the false positive ratio.
Sous-réseauthumb|upright=1.2|Diviser la partie "host number" d'une adresse réseau permet de créer un sous-réseau Un sous-réseau est une subdivision logique d'un réseau de taille plus importante. Le masque de sous-réseau permet de distinguer la partie de l'adresse commune à tous les appareils du sous-réseau et celle qui varie d'un appareil à l'autre. Un sous-réseau correspond typiquement à un réseau local sous-jacent. Historiquement, on appelle également sous-réseau chacun des réseaux connectés à Internet.
Repeated measures designRepeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed. Crossover study A popular repeated-measures design is the crossover study. A crossover study is a longitudinal study in which subjects receive a sequence of different treatments (or exposures).
