normal distributions. Ellett and Brownell (1964) suggest the gamma distribution may be preferred to the lognormal distribution. Eberhardt and Gilbert (1975) made an extensive study of how to distinguish these two distributions and concluded that this is difficult for less than 200 observations. Extensive Monte Carlo simulations were done to reach this conclusion. Forsythe et al. (1975) compared the fit of the gamma and lognormal distributions for the concentration of DDT in earthworms and concluded that both fit the data equally well. Figure 1 shows the similarity of the lognormal and gamma probability density functions for a variety of coefficients of variation and expected value equal 1. Given that both these distributions appear to explain contaminant data equally well, I want to explore the implication of selecting one of these two distributions in estimating the expected value of concentration. Some investigators (Eberhardt and Gilbert, 1973) have suggested using the median of the observed data to measure central tendency when a portion of the samples are below detection limits. I believe that the median may be quite useful for answering some questions, but that usually the expected value is the desired measure. This paper presents the results of Monte Carlo simulations studies of estimating the expected value (EX) for these two distributions. Link and Koch (1975) explored the bias which may result when the lognormal estimator of expected value is used for distributions other than lognormal. They found that a large negative bias (up to 97%) may result when the distribution of the logarithmically transformed variable is heavier tailed than the normal distribution. However, no bias was found when the logarithmically transformed variable has less tail area than the normal distribution. They did not consider lognormal estimation with gamma distributed data. ESTIMATORS First the estimation of EX for the lognormal distribution will be considered. The density function is given by Aitchison and Brown (1976): f(x) = ——1_exp co x vin ¥y - +an x - Wd” 20° ¥ (x > 0;5 06 Oy > 0, -»< My < ) 610 dx