PENERAPAN ANALISIS REGRESI DAN KORELASI DALAM MENENTUKAN ARAH HUBUNGAN ANTARA DUA FAKTOR KUALITATIF PADA TABEL KONTINGENSI [jurnal]
Iwa Sungkawa
Mathematics & Statistics Department, School of Computer Science, Binus University
Jl. K.H. Syahdan No. 9, Palmerah, Jakarta Barat 11480
iwasungkawa@yahoo.com
ABSTRACT
This paper discusses the application of Regression and Correlation Analysis in determining the direction of the relationship between two qualitative factors in the contingency table. As alternatives that can be used in the analysis of Dependence Between Two Qualitative factors are the distribution of chi-square and contingency tables. Levels of dependence and the relationship between the two qualitative factors can be characterized by the results of observations in the contingency table. If all the results of observations in the diagonal table, it can be concluded that there is a strong dependency between the two qualitative factors. However, if the results of observations spread evenly or equally in each cell, will be obtained chi-square value of zero which means the two qualitative factors are
independent. For the observations results of distribution which is uneven and is not collected in the diagonal of contingency table, a test with the chi-square distribution is required. The distribution of chi-square and contingency tables does not detect the direction of the relationship between the two factors, so that the method used to determine the direction of relationship is a regression and correlation analysis. When the regression coefficient and the correlation coefficient is positive, both factors have a direct relationship. Therefore, if one factor increases, other factors will do too, and vice versa. In this study, the two factors are used with ordinal scale, and the level of one of the factors is considered as independent variable and the other as dependent variable. t-test is used to examine the
dependence between qualitative factors, and the significance of the regression and correlation coefficients. Keywords: chi-square distribution, contingency table, correlation coefficient, regression analysis, student’s t
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