a multivariate statistical technique which assesses the similarities between units or assemblages, based on the occurrence or non-occurrence of specific artifact types or other components within them.
A statistical technique that identifies groups of consumers whose characteristics are highly correlated within each cluster grouping and relatively uncorrelated between clusters. Cluster analysis is typically applied to lifestyle characteristics to facilitate the development of a 'bespoke' profile of a marketplace which offers a more 'human' visualisation of consumer groupings than is available via standard industry market research surveys. Links: This commercial American site gives some further information - Clustan.
Techniques that group objects (e.g., pixels) into clusters according to user-defined rules.
multivariate statistical technique often used in segmentation. Respondents are mathematically grouped into clusters, so that people in one cluster are as similar as possible to each other, and as different as possible from people in the other clusters.
Classifies objects so that each object is similar to others in the cluster with respect to some predetermined selection criterion.
A study that puts people or things into a small number of separate groups, so that there will be as much likeness within each group, and as much difference among the groups, as possible.
A method of grouping spatial units or variables measured over spatial units by bringing together the two 'closest' units or variables, the next closest units or variables and so on until all units or variables are in one cluster. The number of clusters finally chosen for further analysis is based on maximizing between cluster differences and minimizing within cluster differences.
A data analysis tool for solving classification problems. Its aim is to sort cases (people, things, events, etc) into groups, or clusters, so that the degree of association is strong between members of the same cluster and weak between members of different clusters. Related Terms: Multivariate analysis technique, Groups BACK
A quantitative research tool used to cluster objects into groups. A common application is market segmentation, wherein respondents are classified according to a variety of characteristics that can range from demographics to usage patterns to attitudes.
a multivariate procedure for detecting natural groupings in data sets, and there are numerous procedures available to accomplish the clustering
Techniques for the purpose of forming similar groups (or clusters) of observations in multivariate data.
A statistical technique that identifies clusters of stocks whose returns are highly correlated within each cluster and relatively uncorrelated across clusters. Cluster analysis has identified groupings such as growth, cyclical, stable, and energy stocks.
a technique for segmenting respondents without using a predictor (dependent) variable. It identifies segments using a variety of data, including attitudinal, usage, or preference inputs. Cluster analysis uses one of several algorithms to group people that are maximally similar to one another and maximally different from other groups. Cluster analysis is best viewed as an exploratory technique, since it is impossible to determine the "right" number of segments for any given market.
A statistical procedure whereby people or items are grouped according to their similarity on measures of interest to the researcher.
a collection of statistical techniques for creating homogeneous groups of cases or variables. Clusters are formed using distance functions. The elements in a cluster have relatively small distances from each other and relatively larger distances from elements outside of a cluster. See distance .
A set of statistical methods in which objects (e.g., compounds) are divided into groups such that objects within a group are similar across a set of 2 or more variables.
is an exploratory data analysis tool that deals with separating data into groups using degree of similarity or difference (distance measure) between individual observations [pg 419-428, 3
A process of assigning data points (e.g., sequences) into groups (clusters), usually starting from the pairwise distances between points.
Cluster analysis is an analytical technique for developing meaningful sub-groups of individuals or objects. Specifically, the objective is to classify a sample of entities (individuals or objects) into a smaller number of mutually exclusive groups based on the similarities among the entities (Hair et al., 1995).
Statistical technique for determining how individuals of a population fall into different groups by making quantitative comparisons of multiple factors.
Cluster analysis is a class of statistical techniques that can be applied to data that exhibits “natural†groupings. Cluster analysis sorts through the raw data and groups them into clusters. A cluster is a group of relatively homogeneous cases or observations.
