When analyze the student data some of the data may seem to be missing. By using a number of techniques such missing data can be brought to line. Among the methods which are used to handle this issue to recover the missing values some popular methods can be adopted, such as CDC (Complete Delete Case), LOCF (Last Observation Carried Forward), RST (Rough Set Technique) and (SS) Soft Set. When data is analyzed in reality mainly three types of missing data occurs depending on the reasons of missingness. They can be classified as MCAR, MAR and MNAR. In order to evaluate the performance of this three usual missing data cases number of similar experiments under a variety of situations where conducted to bring the responsible factors to the surface in this paper. It was noted that the CDC method cannot be used in the data analysis of educational trials. The methods of LOCF and RST are successfully performed under the missing mechanism of MCAR. The methods which can be reliably and comfortably grounded under the MAR missing mechanism are the RST and SS methods.