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 results 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.
