Green's theoremIn vector calculus, Green's theorem relates a line integral around a simple closed curve C to a double integral over the plane region D bounded by C. It is the two-dimensional special case of Stokes' theorem. Let C be a positively oriented, piecewise smooth, simple closed curve in a plane, and let D be the region bounded by C. If L and M are functions of (x, y) defined on an open region containing D and have continuous partial derivatives there, then where the path of integration along C is anticlockwise.
Analysis of varianceAnalysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation.
Conditional expectationIn probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value – the value it would take "on average" over an arbitrarily large number of occurrences – given that a certain set of "conditions" is known to occur. If the random variable can take on only a finite number of values, the "conditions" are that the variable can only take on a subset of those values.
Law of total expectationThe proposition in probability theory known as the law of total expectation, the law of iterated expectations (LIE), Adam's law, the tower rule, and the smoothing theorem, among other names, states that if is a random variable whose expected value is defined, and is any random variable on the same probability space, then i.e., the expected value of the conditional expected value of given is the same as the expected value of .
Algebra of random variablesThe algebra of random variables in statistics, provides rules for the symbolic manipulation of random variables, while avoiding delving too deeply into the mathematically sophisticated ideas of probability theory. Its symbolism allows the treatment of sums, products, ratios and general functions of random variables, as well as dealing with operations such as finding the probability distributions and the expectations (or expected values), variances and covariances of such combinations.
Exponential distributionIn probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the time between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate. It is a particular case of the gamma distribution. It is the continuous analogue of the geometric distribution, and it has the key property of being memoryless. In addition to being used for the analysis of Poisson point processes it is found in various other contexts.
Minimum-variance unbiased estimatorIn statistics a minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than any other unbiased estimator for all possible values of the parameter. For practical statistics problems, it is important to determine the MVUE if one exists, since less-than-optimal procedures would naturally be avoided, other things being equal. This has led to substantial development of statistical theory related to the problem of optimal estimation.
Philippe de VilmorinJoseph-Marie-Philippe Lévêque de Vilmorin (21 May 1872 – 29 June 1917), generally known as Philippe de Vilmorin, was a noted French botanist and plant collector, and a member of the celebrated Vilmorin family of horticulturists. In 1903 Vilmorin began the Arboretum de Pézanin, an arboretum located in Dompierre-les-Ormes, Saône-et-Loire, Bourgogne, France. He also collected plants in Egypt and Sudan that now form part of the herbarium of the National Botanic Garden of Belgium.
Characterizations of the exponential functionIn mathematics, the exponential function can be characterized in many ways. The following characterizations (definitions) are most common. This article discusses why each characterization makes sense, and why the characterizations are independent of and equivalent to each other. As a special case of these considerations, it will be demonstrated that the three most common definitions given for the mathematical constant e are equivalent to each other.
VilmorinVilmorin is a French seed producer. The company has a long history in France, where it was family-controlled for almost two centuries, and today exists as a publicly traded company owned principally by agro-industrial cooperative Groupe Limagrain, the largest plant breeding and seed company in the European Union. Vilmorin was founded as a plant and seed boutique in 1743 by seed expert Claude Geoffroy and her husband Pierre Andrieux, the chief seed supplier and botanist to King Louis XV.
Mapie de Toulouse-LautrecMarie Pierre "Mapie" de Toulouse-Lautrec (1901–1972) was a French journalist and food writer, born Marie Pierre Adélaïde Lévêque de Vilmorin in Verrières-le-Buisson, scion of the Vilmorin seed company. Her horticulturalist father was Joseph Marie Philippe Lévêque de Vilmorin (1872-1917), and her mother was the former Bertha Marie Mélanie de Gaufridy de Dortan (1876-1937). The writer Louise de Vilmorin (1902–1969) was her younger sister, while one of her younger brothers, Roger, was the result of an affair between her mother and Alfonso XIII of Spain.
Dominated convergence theoremIn measure theory, Lebesgue's dominated convergence theorem provides sufficient conditions under which almost everywhere convergence of a sequence of functions implies convergence in the L1 norm. Its power and utility are two of the primary theoretical advantages of Lebesgue integration over Riemann integration. In addition to its frequent appearance in mathematical analysis and partial differential equations, it is widely used in probability theory, since it gives a sufficient condition for the convergence of expected values of random variables.
