Analysis of data in cause and effect relationships

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36414806, 364154, 3641481, 364411, G05B 1302

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active

058503390

ABSTRACT:
A method for analyzing a data set and determining the independent input variables and the values of those variables which are most associated with a specific outcome. Independent and dependent variables may be either numeric (continuous) or categoric (discrete); numeric variables need not be of a specific distribution type. First, each individual independent variable is ranked based on a score. Scoring is done by first determining the number of records in the data set having each of four possible conditions--independent variable in or out of range in combination with dependent variable in or out of range. These values are put into an equation. Iterative processes are used until a high score is found. Subsequently, combinations of variables and values of independent variables are evaluated using the score to determine the combinations most likely to be associated with a specific outcome or range of values of the dependent variable. A use for this method is the determination of manufacturing variables and their values which tend to result in unacceptable product.

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