Salīdzināt metodes

	Perceptuālā un preferenču kartēšana	Atbilstības analīze
Nozare	Statistika	Statistika
Saime	Latent structure	Latent structure
Izcelsmes gads	1979	1984
Autors	John Hauser & Frank Koppelman	Jean-Paul Benzécri; Michael Greenacre
Tips	Multivariate spatial representation	Exploratory multivariate technique for categorical data
Pirmavots	Hauser, J. R., & Koppelman, F. S. (1979). Alternative perceptual mapping techniques: Relative accuracy and usefulness. Journal of Marketing Research, 16(4), 495–506.	Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2
Citi nosaukumi	Perceptual Mapping, Preference Mapping, Attribute-Based Mapping, Algısal Haritalama	CA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum Analizi
Saistītās	3	2
Kopsavilkums	Perceptual and preference mapping is a family of multivariate techniques that simultaneously positions competing objects—brands, products, or stimuli—and respondent preferences within a common low-dimensional space. Introduced systematically by Hauser and Koppelman (1979), the approach lets researchers visualize how consumers perceive attribute-level similarities among objects and which attributes drive individual or segment-level choice. It is widely used in market research, sensory science, and strategic positioning analysis.	Correspondence Analysis (CA) is an exploratory multivariate technique for visualizing the association structure of a two-way contingency table. Developed systematically by Jean-Paul Benzécri in France during the 1960s–1970s and brought to an English-language audience by Michael Greenacre in 1984, CA decomposes the chi-square statistic of a cross-tabulation to produce a low-dimensional joint display — called a biplot — in which rows and columns are represented as points whose proximities reflect their associations.