Mathematics and Statistics Vol. 8(2A), pp. 1 - 8
DOI: 10.13189/ms.2020.081301
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The Performance of Different Correlation Coefficient under Contaminated Bivariate Data

Bahtiar Jamili Zaini ^*, Shamshuritawati Sharif
School of Quantitative Sciences, Universiti Utara Malaysia, Malaysia

ABSTRACT

Bivariate data consist of 2 random variables that are obtained from the same population. The relationship between 2 bivariate data can be measured by correlation coefficient. A correlation coefficient computed from the sample data is used to measure the strength and direction of a linear relationship between 2 variables. However, the classical correlation coefficient results are inadequate in the presence of outliers. Therefore, this study focuses on the performance of different correlation coefficient under contaminated bivariate data to determine the strength of their relationships. We compared the performance of 5 types of correlation, which are classical correlations such as Pearson correlation, Spearman correlation and Kendall’s Tau correlation with other robust correlations, such as median correlation and median absolute deviation correlation. Results show that when there is no contamination in data, all 5 correlation methods show a strong relationship between 2 random variables. However, under the condition of data contamination, median absolute deviation correlation denotes a strong relationship compared to other methods.

KEYWORDS
Bivariate, Contaminated Data, Correlation, Robust Correlation

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Bahtiar Jamili Zaini , Shamshuritawati Sharif , "The Performance of Different Correlation Coefficient under Contaminated Bivariate Data," Mathematics and Statistics, Vol. 8, No. 2A, pp. 1 - 8, 2020. DOI: 10.13189/ms.2020.081301.

(b). APA Format:
Bahtiar Jamili Zaini , Shamshuritawati Sharif (2020). The Performance of Different Correlation Coefficient under Contaminated Bivariate Data. Mathematics and Statistics, 8(2A), 1 - 8. DOI: 10.13189/ms.2020.081301.