assumed

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 = standard error of the observation divided by the mean value of the observation in natural space), then the value of standard error in log space can be calculated as $\sqrt{(log_e(1+(CV)^2))}$.
+Abundance indices typically assumed to 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 = standard error of the observation divided by the mean value of the observation in natural space), then the value of standard error in log space can be calculated as $\sqrt{(log_e(1+(CV)^2))}$.
 
 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.