The objective pursued in this article is to study Correspondence Factor Analysis (CA), which is an extremely powerful tool for synthesizing information, widely used when dealing with a large mass of qualitative data. treat.
It also makes it possible to identify existing relationships between individuals by evaluating their similarities, as well as relationships between variables by evaluating their connections, and obtain a simple representation of the data cloud in a low-dimensional space closer to reality.
Factorial analysis of the data was applied using R software, version 4.3.1 (2023-06-16 ucrt).
The application of the said method was carried out on «the nutritional status of Congolese children under 5 years old, from January to December 2022, PRONANUT, DR Congo».
The data was summarized in a table of 26 row categories and 12 column categories. The 26 rows (individuals) represent the health provinces of DR Congo and the 12 columns, the variables relating to the activities of the PRONANUT Preschool Consultation.