Testing for Zero Correlation between Two Uncorrelated Non-Linearly Dependent Random Variables: A Cautionary Note

Authors

  • Umberto Triacca Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L’Aquila, Italy

Keywords:

Student’s t-test, Pearson correlation coefficient, normality assumption

Abstract

A simulation study was performed to analyze the effects of violations of the normality assumption on the t-test of the Pearson correlation coefficient when the variables are not independent, even though the population correlation is zero. Large effects for violations of normality were found. The Type I error rate can be either inflated or deflated with respect to the assumed error rate. A recommendation is made that the use of the t-test be avoided where there are good reasons to believe that a nonlinear relationship exists between the variables.

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Published

2017-07-08

How to Cite

Triacca, U. (2017). Testing for Zero Correlation between Two Uncorrelated Non-Linearly Dependent Random Variables: A Cautionary Note. Thailand Statistician, 15(2), 196–202. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/92213

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Articles