Open AccessContribution of a categorical statistical test in examining dependencies among qualitative variables by means simplification of correspondence analysis
Author(s) -
Irlandia Ginanjar,
I. Nurhuda,
Neneng Sunengsih,
Sudartianto
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1265/1/012022
Subject(s) - correspondence analysis , contingency table , categorical variable , multiple correspondence analysis , mathematics , principal component analysis , matrix (chemical analysis) , principal (computer security) , test (biology) , qualitative analysis , statistics , qualitative research , computer science , paleontology , social science , materials science , sociology , composite material , biology , operating system
The contribution statistical test of categories to dependencies between qualitative variables is needed, because the existence of these categories will influence decision making. Decisions taken can be misleading, if a category does not contribute. If N is the matrix from 2×J or I×2 contingency table which is constructed from two qualitative variables, then the principal coordinates can be calculated using the simplification of correspondence analysis (SoCA). Principal coordinates produced by the SoCA are the same as conventional correspondence analysis (CA), but the SoCA presents a simpler calculation, because it is calculated directly from the elements of N . Principal coordinates derived from 2×J matrix N can be used to test the contribution of categories to dependencies between qualitative variables more simply, and obtained confidence intervals for each category.