Workshop Introduction:
This workshop aims to introduce participants to practical techniques for detecting and treating outliers in datasets using SPSS. Outliers often distort statistical estimates such as the mean and standard deviation, which in turn affects the significance of the analysis and may lead to inaccurate conclusions and decisions. The session is particularly designed for researchers and postgraduate students seeking to improve the accuracy and reliability of their statistical analyses.
Workshop Topics:
Introduction to Outliers: Definition, Causes, Types, and Their Impact on Statistical Results
Methods for Detecting Outliers (Four Techniques with Applications in SPSS)
Strategies for Handling and Treating Outliers (with Applications in SPSS)
Trainer:
Dr. Mohamed Abdel Nabi Bargal
Faculty of Agriculture, Alexandria University – Egypt
Trainer’s Short Bio:
PhD in Agricultural Sciences from the Faculty of Agriculture, Alexandria University.
Lecturer in the Department of Agricultural Extension Education, Faculty of Agriculture, Alexandria University.
Dr. Bargal specializes in applied statistics and educational research within agricultural contexts, with a focus on training researchers and postgraduate students in modern data analysis tools and techniques.