This blog talks about the major applications of Discriminant Analysis and how effectively it is used in various businesses.
This technique is used in order to distinguish between two or three sets of objects or people, based on some knowledge of there characteristics.
Discriminant function analysis is used to determine which variables discriminate between two or more naturally occurring group. For example, an educational researcher may want to investigate which variables discriminate between high school graduates who decide (1) to go to college, (2) to attend a trade or professional school, or (3) to seek no further training or education. For that purpose the researcher could collect data on numerous variables prior to students' graduation. After graduation, most students will naturally fall into one of the three categories. Discriminant Analysis could then be used to determine which variable(s) are the best predictors of students' subsequent educational choice.
A medical researcher may record different variables relating to patients' backgrounds in order to learn which variables best predict whether a patient is likely to recover completely (group 1), partially (group 2), or not at all (group 3). A biologist could record different characteristics of similar types (groups) of flowers, and then perform a discriminant function analysis to determine the set of characteristics that allows for the best discrimination between the types.
Discriminant analysis can be, and is in fact used by credit rating agencies to rate individuals, to classify them according to good lending risk or bad lending risk.
Submitted by
Nikhil Malhotra
This technique is used in order to distinguish between two or three sets of objects or people, based on some knowledge of there characteristics.
Discriminant function analysis is used to determine which variables discriminate between two or more naturally occurring group. For example, an educational researcher may want to investigate which variables discriminate between high school graduates who decide (1) to go to college, (2) to attend a trade or professional school, or (3) to seek no further training or education. For that purpose the researcher could collect data on numerous variables prior to students' graduation. After graduation, most students will naturally fall into one of the three categories. Discriminant Analysis could then be used to determine which variable(s) are the best predictors of students' subsequent educational choice.
A medical researcher may record different variables relating to patients' backgrounds in order to learn which variables best predict whether a patient is likely to recover completely (group 1), partially (group 2), or not at all (group 3). A biologist could record different characteristics of similar types (groups) of flowers, and then perform a discriminant function analysis to determine the set of characteristics that allows for the best discrimination between the types.
Discriminant analysis can be, and is in fact used by credit rating agencies to rate individuals, to classify them according to good lending risk or bad lending risk.
Submitted by
Nikhil Malhotra
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