COMPARISON OF SPURIOUS CORRELATION METHODS USING PROBABILITY DISTRIBUTOINS AND PROPORTION OF REJECTING A TRUE NULL HYPOTHESIS

Abstract

The problem of spurious correlation analysis, e.g. Pearson moment - product correlation test is that, the data need to be normally distributed. This research work compares spurious correlation methods using some non - normal probability distributions in order to obtain the method with the best degree of association among them. The methods were compared using proportions of rejecting true null hypothesis obtained from t and z test statistics for testing correlation coefficients. Data from Normal, log - normal, exponential and contaminated normal distributions were generated using simulation method with different sample sizes. The result s indicate that, when the data are normal, exponential and contaminated normal random distributions, Pearson's and Spearman's rank have the best proportion of rejecting the true null hypothesis . But , when the data are log - normal distribution, only Spearman's rank correlation coefficient has the best proportion of rejecting the true null hypothesis. Thus , Pearson's and Spearman's rank have the best degree of association under normal, exponential and contaminated normal distributions . While , for log-normal distribution only Spearman's rank has the best degree of association.