Volume 41, Issue 4, February 2024, Pages 1088–1097
Don Folly FOFOLO Mulembu1, Rostin MABELA Makengo Matendo2, Fidèle MUAKU Mvunzi3, Grace NKWESE Mazoni4, and Camile LIKOTELO BINENE5
1 Dpt. Computer Science & Mathematics, Technical Section, ISP Kikwit, RD Congo
2 Dpt. Mathematics, Statistics and Computer Science, Faculty of Science and Technology, University of Kinshasa, RD Congo
3 Dpt. Mathematics, Statistics and Computer Science, Faculty of Science and Technology, National Pedagogical University of Kinshasa Ngaliema, RD Congo
4 Dpt. Mathematics, Statistics and Computer Science, Faculty of Science and Technology, National Pedagogical University of Kinshasa Ngaliema, RD Congo
5 Dpt. Mathematics, Statistics and Computer Science, Faculty of Science and Technology, National Pedagogical University of Kinshasa Ngaliema, RD Congo
Original language: English
Copyright © 2024 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.
Author Keywords: Data analysis, Factorial correspondence analysis, Nutritional status of Congolese children under 5 years old.
Don Folly FOFOLO Mulembu1, Rostin MABELA Makengo Matendo2, Fidèle MUAKU Mvunzi3, Grace NKWESE Mazoni4, and Camile LIKOTELO BINENE5
1 Dpt. Computer Science & Mathematics, Technical Section, ISP Kikwit, RD Congo
2 Dpt. Mathematics, Statistics and Computer Science, Faculty of Science and Technology, University of Kinshasa, RD Congo
3 Dpt. Mathematics, Statistics and Computer Science, Faculty of Science and Technology, National Pedagogical University of Kinshasa Ngaliema, RD Congo
4 Dpt. Mathematics, Statistics and Computer Science, Faculty of Science and Technology, National Pedagogical University of Kinshasa Ngaliema, RD Congo
5 Dpt. Mathematics, Statistics and Computer Science, Faculty of Science and Technology, National Pedagogical University of Kinshasa Ngaliema, RD Congo
Original language: English
Copyright © 2024 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
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.
Author Keywords: Data analysis, Factorial correspondence analysis, Nutritional status of Congolese children under 5 years old.
How to Cite this Article
Don Folly FOFOLO Mulembu, Rostin MABELA Makengo Matendo, Fidèle MUAKU Mvunzi, Grace NKWESE Mazoni, and Camile LIKOTELO BINENE, “Application of Correspondence Factor Analysis (CA) on data on the nutritional status of children under 5 years old, PRONANUT, from January to December 2022 in DR Congo,” International Journal of Innovation and Applied Studies, vol. 41, no. 4, pp. 1088–1097, February 2024.
