• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.395-407
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• 2007

Outliers distort many measures for data analysis. We can propose dandelion seed plot as a graphical tool for evaluating the effect of outliers in one-and two-variate data. We can draw mean-variance dandelion seed plots using linked curves which are made by changing weights from 1 to 0 for each datum. Similarly we can also draw covariance-correlation-coefficient dandelion seed plots. This graphical method can be a useful tool for elementary statistics education in college.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.221-226
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• 2006

We usually use two techniques(influence function and local influence) for detecting outliers. But, we cannot use these difficult techniques in elementary industrial statistics course for college students. We can use some simple graphical methods(box plot, dandelion seed plot, influence graph and cumulative deletion plot) for univariate and bivariate outlier detection and outlier effect in elementary industrial statistics course for college students.