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'''CHAID''' is a type of [[decision tree]] technique. It was published in [[1980]] by Gordon V. Kass. It can be used for prediction (like [[regression analysis]]) or for detection of interaction between variables. CHAID stands for '''CH'''i-squared '''A'''utomatic '''I'''nteraction '''D'''etector.
'''CHAID''' is a technique that detects interaction between variables. It is used to identify discrete groups of consumer and predict how their responses to some variables affect other variables. ▼
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CHAID detects interaction between variables in the data set. Using this technique we can establish relationships between a ‘dependent variable’ – for example readership of a certain newspaper – and other explanatory variables such as price, size, supplements etc. CHAID does this by identifying discrete groups of respondents and, by taking their responses to explanatory variables, seeks to predict what the impact will be on the dependent variable.
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=See also:=
*[[Chi-square distribution]]
*[[Decision tree]]▼
*[[Latent class model]]
*[[Structural equation modeling]]
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[[Category:Statistical algorithms]]
[[Category:Regression analysis]]
[[Category:Classification algorithms]]
[[de:CHAID]]
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