Multiple Imputation Method for Missing Data

Department of Business Administration held a seminar titled “Multiple Placement Method for Missing Data” by Dr. Hawker Kassem Bairdawood, who explained how incomplete data is a very serious problem in many areas of research, such as active media technology, surveys, market research surveys, Medical studies, and other scientific experiments. Missing data often complicate scientific investigations. The development of statistical methods for processing lost data has been an active field of research in recent decades. Determining the appropriate analytical approach in the presence of incomplete observations is a key question for data analysts. Determining the appropriate analytical approach in the presence of incomplete observations is a key question for data analysts. Multi-initiation (MI) seems to be one of the most attractive methods for dealing with the general purposes of missing data in the univariate and multivariate analysis. The seminar was attended by members of the department