Differences between pearson's product moment correlation coefficient and an absolute value correlation coefficient in the presence of outliers / Norafefah Mohamad Sobri ...[et al]

The correlation coefficient is one of the most commonly used statistical measures in all branches of statistics. The empirical evidence shows that this correlation coefficient is sufficiently non-robust against outliers. The aimof this study is to compare the performance of the estimator of correlat...

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Bibliographic Details
Main Authors: Mohamad Sobri, Norafefah (Author), Midi, Prof Dr. Habshah (Author), Ibrahim, Nurul Bariyah (Author), Ismail, Nor Azima (Author)
Format: Book
Published: Unit Penerbitan UiTM Kelantan, 2016-06.
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100 1 0 |a Mohamad Sobri, Norafefah  |e author 
700 1 0 |a Midi, Prof Dr. Habshah  |e author 
700 1 0 |a Ibrahim, Nurul Bariyah  |e author 
700 1 0 |a Ismail, Nor Azima  |e author 
245 0 0 |a Differences between pearson's product moment correlation coefficient and an absolute value correlation coefficient in the presence of outliers / Norafefah Mohamad Sobri ...[et al] 
260 |b Unit Penerbitan UiTM Kelantan,   |c 2016-06. 
500 |a https://ir.uitm.edu.my/id/eprint/29583/1/29583.pdf 
520 |a The correlation coefficient is one of the most commonly used statistical measures in all branches of statistics. The empirical evidence shows that this correlation coefficient is sufficiently non-robust against outliers. The aimof this study is to compare the performance of the estimator of correlation coefficient. In this study, Pilot-plant data was considered at first stage. Second stage of this study, the simulation data were generated based on normal and uniform distributionat its four contaminated form. The methods of analysis used in this study were Pearson's correlation coefficient and An Absolute Value correlation coefficient. It can be conclude that an Absolute Value correlation coefficient performs well and more robustcompared to Pearson's correlation coefficient in existence of outliers. Then we investigated the bias, standard error (SE) and root mean square error (RMSE) to judge their performance. The result shows that an Absolute Value performs better than Pearson's correlation coefficient. In general An Absolute Value correlation coefficient appears to be a good estimator because it has the lowest values of bias, standard error and RMSE 
546 |a en 
690 |a HA Statistics 
690 |a Regression. Correlation 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
787 0 |n https://ir.uitm.edu.my/id/eprint/29583/ 
787 0 |n https://jmcs.com.my/ 
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