Types of Unusual Observations in Multiple Regression & Some Methods of it’s Diagnostic with Application

The work in this paper is a diagnosis of three types of unusual observations in multiple regression, the outlier observation is diagnostic by using Boxplot & studentized residuals, Diagnostic leverage points by using (Hat matrix) , & diagnostic of the influence observations by using (dfbeta).In practice the work is comparing the effects of omitting outlier observations in the normal distribution of the residuals to the equation which is building to the Thalassaemia disease and Treating the multicollinearity by omitting some variables and using ridge regression, getting a good model agrees with the viewing of medicine by using (SAS.9) package.