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8data.tex

@@ -435,7 +435,7 @@ \subsection{Indices}
 		\item >0 = Student's t-distribution in log space with degrees of freedom equal to this value. For DF>30, results will be nearly identical to that for lognormal distribution. A DF value of about 4 gives a fat-tail to the distribution. The standard error values entered in the data file must be the standard error in log\textsubscript{e} space.
 	\end{itemize}
 
-Abundance indices typically have a lognormal error structure with units of standard error of log\textsubscript{e}(index). If the variance of the observations is available only as a coefficient of variation (CV) in natural space, then the value of standard error in log space can be calculated as $\sqrt{(log(1+(CV)^2))}$ where the CV is the standard error of the observation divided by the mean value of the observation.
+Abundance indices typically have a lognormal error structure with units of standard error of log\textsubscript{e}(index). If the variance of the observations is available only as a coefficient of variation (CV) in natural space, then the value of standard error in log space can be calculated as $\sqrt{(log(1+(CV)^2))}$ where the CV is the standard error of the observation divided by the mean value of the observation in natural space.
 
 For the normal error structure, the entered values for standard error are interpreted directly as a standard error in arithmetic space and not as a CV. Thus switching from a lognormal to a normal error structure forces the user to provide different values for the standard error input in the data file.