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.
