Al-Furat Al-Awsat Technical University concludes a scientific course on nonparametric tests in the Spss program

The Department of Community Health Technologies at the College of Health and Medical Technologies/Kufa, one of the formations of Al-Furat Al-Awsat Technical University, concluded the training course in advanced statistics, in the field of nonparametric tests within the SPSS program, which lasted for three days to cover the requirements of the course. A group of the department’s teachers took turns giving lectures.

The course aimed to provide participants with data analysis skills and techniques that do not depend on initial assumptions such as the normal distribution of data. The emphasis is on the use of statistical tests that do not assume a particular form of data, which makes it a powerful tool for analyzing data that does not fit the usual assumptions of parametric tests.
The course covered important topics such as: basic non-parametric tests such as the Mann-Whitney U test to test the differences between two independent groups, the Wilcoxo Signed-Rank test to test the differences between two related groups, in addition to the Kruskal-Wallis test to compare more than two groups.
The course also touched on practical applications how to apply these tests to real data in various fields such as health, social sciences, commerce and comparison with scientific tests by identifying the fundamental differences between parametric and non-parametric tests, and the appropriate time to use each of them.
The course recommended that participants continue to apply non-teacher tests to various data sets to enhance understanding and improve their skills. Paying attention to the correct interpretation of the results, keeping abreast of technical developments, promoting interdisciplinary cooperation and encouraging researchers and practitioners in various fields to use non-parametric tests to analyze data in their own fields, which enhances the accuracy and quality of the results.
Government information and Communication Division
Faculty of Health and medical technologies / Kufa