دراسة تطبيقية لتحليل التمايز في بعض النماذج الإحصائية

An Applied Study to Analyze Discriminant in Some Statistical Models

The discriminate analysis is a statistical method based on a sample of observations taken from known societies to build a base that can help in identifying the society to which the new observations belong based on variables with discriminatory characteristics and applied to diagnose three types of tumors, namely breast, vertebral column (bone) and the respiratory system (lung) tumors as their prevalent in our society is abundance nowadays.

For the purpose of studying this subject, the values ​​of observations were recorded for five variables (sex, age, occupation, prognosis and duration of hospitalization) for 270 patients (random samples) and they were studied in four statistical models. The models were (linear discrimination function) and nonlinear (quadratic discrimination function and logistic discrimination function) and non-parametric model (nearest neighbor function).

 The statistical results were derived from the statistical program Stata as well as the statistical package SPSS to classify the tumors to which group they belong. The classification error criterion was used as a criterion for comparison between the four models, to the best model with the least error of invention in possible.

It was found that the nearest neighbor model was superior to the rest of the models in terms of lack of classification of the wrong as compared to other models.