Cluster samplingIn statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population. It is often used in marketing research. In this sampling plan, the total population is divided into these groups (known as clusters) and a simple random sample of the groups is selected. The elements in each cluster are then sampled. If all elements in each sampled cluster are sampled, then this is referred to as a "one-stage" cluster sampling plan.
Échantillonnage (statistiques)thumb|Exemple d'échantillonnage aléatoire En statistique, l'échantillonnage désigne les méthodes de sélection d'un sous-ensemble d'individus (un échantillon) à l'intérieur d'une population pour estimer les caractéristiques de l'ensemble de la population. Cette méthode présente plusieurs avantages : une étude restreinte sur une partie de la population, un moindre coût, une collecte des données plus rapide que si l'étude avait été réalisé sur l'ensemble de la population, la réalisation de contrôles destructifs Les résultats obtenus constituent un échantillon.
Circle packing theoremThe circle packing theorem (also known as the Koebe–Andreev–Thurston theorem) describes the possible tangency relations between circles in the plane whose interiors are disjoint. A circle packing is a connected collection of circles (in general, on any Riemann surface) whose interiors are disjoint. The intersection graph of a circle packing is the graph having a vertex for each circle, and an edge for every pair of circles that are tangent.
Universal vertexIn graph theory, a universal vertex is a vertex of an undirected graph that is adjacent to all other vertices of the graph. It may also be called a dominating vertex, as it forms a one-element dominating set in the graph. (It is not to be confused with a universally quantified vertex in the logic of graphs.) A graph that contains a universal vertex may be called a cone. In this context, the universal vertex may also be called the apex of the cone.
Graphe bipartiEn théorie des graphes, un graphe est dit biparti si son ensemble de sommets peut être divisé en deux sous-ensembles disjoints et tels que chaque arête ait une extrémité dans et l'autre dans . Un graphe biparti permet notamment de représenter une relation binaire. Il existe plusieurs façons de caractériser un graphe biparti. Par le nombre chromatique Les graphes bipartis sont les graphes dont le nombre chromatique est inférieur ou égal à 2. Par la longueur des cycles Un graphe est biparti si et seulement s'il ne contient pas de cycle impair.
Shallow minorIn graph theory, a shallow minor or limited-depth minor is a restricted form of a graph minor in which the subgraphs that are contracted to form the minor have small diameter. Shallow minors were introduced by , who attributed their invention to Charles E. Leiserson and Sivan Toledo. One way of defining a minor of an undirected graph G is by specifying a subgraph H of G, and a collection of disjoint subsets Si of the vertices of G, each of which forms a connected induced subgraph Hi of H.
Bounded expansionIn graph theory, a family of graphs is said to have bounded expansion if all of its shallow minors are sparse graphs. Many natural families of sparse graphs have bounded expansion. A closely related but stronger property, polynomial expansion, is equivalent to the existence of separator theorems for these families. Families with these properties have efficient algorithms for problems including the subgraph isomorphism problem and model checking for the first order theory of graphs.
Nonprobability samplingSampling is the use of a subset of the population to represent the whole population or to inform about (social) processes that are meaningful beyond the particular cases, individuals or sites studied. Probability sampling, or random sampling, is a sampling technique in which the probability of getting any particular sample may be calculated. In cases where external validity is not of critical importance to the study's goals or purpose, researchers might prefer to use nonprobability sampling.
Forbidden graph characterizationIn graph theory, a branch of mathematics, many important families of graphs can be described by a finite set of individual graphs that do not belong to the family and further exclude all graphs from the family which contain any of these forbidden graphs as (induced) subgraph or minor. A prototypical example of this phenomenon is Kuratowski's theorem, which states that a graph is planar (can be drawn without crossings in the plane) if and only if it does not contain either of two forbidden graphs, the complete graph K_5 and the complete bipartite graph K_3,3.
Nombre de croisements (théorie des graphes)vignette| Une représentation du graphe de Heawood avec trois croisements. C'est le nombre minimum de croisements parmi toutes les représentations de ce graphe, qui a donc un nombre de croisements . En théorie des graphes, le nombre de croisements d'un graphe G est le plus petit nombre d'intersections d'arêtes d'un tracé du graphe G. Par exemple, un graphe est planaire si et seulement si son nombre de croisements est nul. La détermination du nombre de croisements tient une place importante dans le tracé de graphes.
