This payer reviews four commonly used statistical methods for environmental
data analysis and discusses potential pitfalls associated with application
of these methods through real case study data. The four statistical method
s are percentile and confidence interval, correlation coefficient, regressi
on analysis, and analysis of variance (ANOVA). The potential pitfall for es
timation of percentile and confidence interval includes the automatic assum
ption of a normal distribution to environmental data, which so often show a
log-normal distribution. The potential pitfall for correlation coefficient
includes the use of a wide range of data points in which the maximum in va
lue may trivialize other smaller data points and consequently skew the corr
elation coefficient. The potential pitfall for regression analysis includes
the propagation of uncertainties of input variables to the regression mode
l prediction, which may be even more uncertain. The potential pitfall for A
NOVA includes the acceptance of a hypothesis as a weak argument to imply a
strong conclusion. As demonstrated in this paper, we may draw very differen
t conclusions based on statistical analysis if the pitfalls are not identif
ied. Reminder and enlightenment obtained from the pitfalls are given at the
end of this article. (C) 2000 AEHS.