بناء الدالة التمييزية : مراجعة مقال

Abstract EN

Discriminant Analysis has been widely used to classify data into subgroups based on certain criteria.

The classification process depends on choosing any variable that shows a statistical significance, then use the selected variables to build the discriminant function.

In order to investigate the statistical significance of the variables in our data, we used RoyBose procedure for finding confidence intervals and t-test, which is one of the popular variable-selection methods in discriminant analysis.

In addition, some other variableselection techniques has been employed, namely, Forward-Selection, Backward-Selection, and Stepwise-Selection methods, which are usually used to select variables in linear regression analysis.

Furthermore, a principal component analysis has been carried out for the purpose of choosing the variables with high statistical significance.

The selected variables have been used to build the discriminant function.