Abstract
Observed radon gas levels typically demonstrate a skewed sampling distribution. Traditional analyses to compare mean or median radon levels among different demographic groups rely on transformations of these data. The logarithmic transformation is one that is traditionally employed. Unfortunately, transformations such as the logarithmic tend to de-emphasize extreme values. In radon gas research, these extreme values are of primary interest. The proposed methodology is based on characterizing the sampling distribution of radon levels by a non-normal distribution. The mean radon level is estimated based on the assumed sampling distribution. Comparisons among groups are considered through a weighted analysis of variance. Results of a survey conducted by the state of Kansas are used as an example.
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