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Multiple Correspondence Analysis
In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space. The procedure thus appears to be the counterpart of principal component analysis for categorical data. MCA can be viewed as an extension of simple correspondence analysis (CA) in that it is applicable to a large set of categorical variables. As an extension of correspondence analysis MCA is performed by applying the CA algorithm to either an indicator matrix (also called ''complete disjunctive table'' – CDT) or a ''Burt table'' formed from these variables. An indicator matrix is an individuals × variables matrix, where the rows represent individuals and the columns are dummy variables representing categories of the variables. Analyzing the indicator matrix allows the direct representation of individuals as points in ge ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Jean-Paul Benzécri
Jean-Paul Benzécri was a French people, French mathematician and statistician. He studied at École Normale Supérieure and was professor at University of Rennes 1, Université de Rennes and later for most of his career at the Paris Institute of Statistics (l'Institut de Statistique de l'Université de Paris), Université Pierre-et-Marie-Curie in Paris. He is most known for his specific inductive approach to data analysis which led to the creation of Correspondence analysis, a statistical technique for analyzing contingency tables and for the invention of the nearest-neighbor chain algorithm for agglomerative hierarchical clustering. Early life Jean-Paul Benzécri was born in Oran, Algeria, in 1932, where his father was a doctor. He attended high school in Lycée Lamoricière, Oran and Lycée Bugeaud, Alger. In 1950, he was first in the entrance examination to the ENS (École Normale Supérieure) in Paris and again in 1953 to the "Agrégation de Mathématiques", a national teacher ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Field (Bourdieu)
In sociology, field theory examines how individuals construct social fields, and how they are affected by such fields. Social fields are environments in which competition between individuals and between groups takes place, such as markets, academic disciplines, musical genres, etc. Fields feature different positions that social actors can occupy. The dominant players in the field, called the ''incumbents'', are generally invested in maintaining the field in its current form, as changes to the rules of competition risk destabilizing their dominant position.Cattani, Gino, Simone Ferriani, and Paul Allison. 2014.Insiders, Outsiders and the Struggle for Consecration in Cultural Fields: A Core-Periphery Perspective" ''American Sociological Review'' 78(3):417–47. Archived via Google Docs Fields may also feature ''insurgents'' who instead aim to alter the field so they can successfully compete with the incumbents. Fligstein, Neil. 2001. "Social Skill and the Theory of Fields." ''Soci ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
The State Nobility
''The'' () is a grammatical article in English, denoting persons or things already mentioned, under discussion, implied or otherwise presumed familiar to listeners, readers, or speakers. It is the definite article in English. ''The'' is the most frequently used word in the English language; studies and analyses of texts have found it to account for seven percent of all printed English-language words. It is derived from gendered articles in Old English which combined in Middle English and now has a single form used with pronouns of any gender. The word can be used with both singular and plural nouns, and with a noun that starts with any letter. This is different from many other languages, which have different forms of the definite article for different genders or numbers. Pronunciation In most dialects, "the" is pronounced as (with the voiced dental fricative followed by a schwa) when followed by a consonant sound, and as (homophone of pronoun ''thee'') when followed by a v ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
La Distinction
''Distinction: A Social Critique of the Judgement of Taste'' (''La Distinction: Critique sociale du jugement'', 1979) by Pierre Bourdieu, is a sociological report about the state of French culture, based upon the author's empirical research from 1963 until 1968. The English translation was published in 1984, and, in 1998, the International Sociological Association voted ''Distinction'' as an important book of sociology published in the 20th century. Summary As a social critique of the judgements of taste, ''Distinction'' (1979) proposes that people with much cultural capital — education and intellect, style of speech and style of dress, etc. — participate in determining what distinct aesthetic values constitute '' good taste'' within their society. Circumstantially, people with less cultural capital accept as natural and legitimate that ruling-class definition of ''taste'', the consequent distinctions between high culture and low culture, and their restrictions upon the social ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pierre Bourdieu
Pierre Bourdieu (; 1 August 1930 – 23 January 2002) was a French sociologist and public intellectual. Bourdieu's contributions to the sociology of education, the theory of sociology, and sociology of aesthetics have achieved wide influence in several related academic fields (e.g. anthropology, media and cultural studies, education, popular culture, and the arts). During his academic career he was primarily associated with the School for Advanced Studies in the Social Sciences in Paris and the Collège de France. Bourdieu's work was primarily concerned with the dynamics of power in society, especially the diverse and subtle ways in which power is transferred and social order is maintained within and across generations. In conscious opposition to the idealist tradition of much of Western philosophy, his work often emphasized the corporeal nature of social life and stressed the role of practice and embodiment in social dynamics. Building upon and criticizing the theories of Kar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Factor Analysis Of Mixed Data
In statistics, factor analysis of mixed data or factorial analysis of mixed data (FAMD, in the French original: ''AFDM'' or ''Analyse Factorielle de Données Mixtes''), is the factorial method devoted to data tables in which a group of individuals is described both by quantitative and qualitative variables. It belongs to the exploratory methods developed by the French school called ''Analyse des données'' (data analysis) founded by Jean-Paul Benzécri. The term ''mixed'' refers to the use of both quantitative and qualitative variables. Roughly, we can say that FAMD works as a principal components analysis (PCA) for quantitative variables and as a multiple correspondence analysis (MCA) for qualitative variables. Scope When data include both types of variables but the active variables being homogeneous, PCA or MCA can be used. Indeed, it is easy to include supplementary quantitative variables in MCA by the correlation coefficients between the variables and factors on individuals ( ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cluster Analysis
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistics, statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis itself is not one specific algorithm, but the general task to be solved. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small Distance function, distances between cluster members, dense areas of the data space, intervals or particular statistical distributions. Clustering can therefore be formulated as a multi-object ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Geometric Data Analysis
Geometric data analysis comprises geometric aspects of image analysis, pattern analysis, and shape analysis, and the approach of multivariate statistics, which treat arbitrary data sets as ''clouds of points'' in a space that is ''n''-dimensional. This includes topological data analysis, cluster analysis, inductive data analysis, correspondence analysis, multiple correspondence analysis, principal components analysis and See also * Algebraic statistics for algebraic-geometry in statistics *Combinatorial data analysis *Computational anatomy for the study of shapes and forms at the morphome scale *Structured data analysis (statistics) Structured data analysis is the statistical data analysis of structured data. This can arise either in the form of an ''a priori'' structure such as multiple-choice questionnaires or in situations with the need to search for structure that fits t ... References * * Approximation of Geodesic Distances for Geometric Data Analysis Differential geom ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Eigenvalues
In linear algebra, an eigenvector () or characteristic vector of a linear transformation is a nonzero vector that changes at most by a scalar factor when that linear transformation is applied to it. The corresponding eigenvalue, often denoted by \lambda, is the factor by which the eigenvector is scaled. Geometrically, an eigenvector, corresponding to a real nonzero eigenvalue, points in a direction in which it is stretched by the transformation and the eigenvalue is the factor by which it is stretched. If the eigenvalue is negative, the direction is reversed. Loosely speaking, in a multidimensional vector space, the eigenvector is not rotated. Formal definition If is a linear transformation from a vector space over a field into itself and is a nonzero vector in , then is an eigenvector of if is a scalar multiple of . This can be written as T(\mathbf) = \lambda \mathbf, where is a scalar in , known as the eigenvalue, characteristic value, or characteristic root ass ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Analysis
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering ne ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Factor Analysis
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observed variables mainly reflect the variations in two unobserved (underlying) variables. Factor analysis searches for such joint variations in response to unobserved latent variables. The observed variables are modelled as linear combinations of the potential factors plus "error" terms, hence factor analysis can be thought of as a special case of errors-in-variables models. Simply put, the factor loading of a variable quantifies the extent to which the variable is related to a given factor. A common rationale behind factor analytic methods is that the information gained about the interdependencies between observed variables can be used later to reduce the set of variables in a dataset. Factor analysis is commonly used in psychometrics, persona ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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