Evaluation System (ODES) maintained by EPA's Office of Marine and 

 Estuarine Protection (Tetra Tech 1986d). The measure used to 

 evaluate the statistical sensitivity of the monitoring design was the 

 minimum detectable difference between two mean values. To general- 

 ize the results of the power analysis, the minimum detectable difference 

 was expressed as a percentage of the grand mean among treatments. 

 The power of the test was fixed at 0.80. 



Predicted values of minimum detectable difference are shown for 

 various levels of sample replication m Figures E-1 and E-2. For these 

 analyses, the Type I error was fixed at 0.05. Minimum detectable 

 difference was plotted vs. number of replicate samples for the following 

 cases: 



• Number of stations (or sampling times) equal to 4, 6, 8, and 16 

 stations (or times) 



• Data Variability Coefficient (across treatments) equal to 30, 

 50, 70, and 90 percent. 



The Data Variability Coefficient is equal to the within-groups mean 

 square divided by the grand mean among groups (and multipHed by 

 100 to convert to a percentage). In designing a bioaccumulation study, 

 the Data Variability Coefficient can be estimated by performing an 

 ANO VA on available data from the literature or on a preliminary data 

 set. If such data cannot be obtained, the average Coefficient of Varia- 

 tion (within groups) can be used as a rough estimate of the Data 

 Variability Coefficient. 



The effect of setting a different value for Type I error is shown in Figure 

 E-3. The effect of changes in Type I error is greater for higher levels 

 of data variability. Note that substantial increases in sensitivity (i.e., 

 decreases in minimum detectable difference) are achieved only for the 

 case of three replicate samples in Figure E-3. 



