noyance of single presentations of test signals. Suppose, for example, that 1,000 annoyance judgments are solicited by asking 50 test subjects 20 times each during the course of a laboratory experiment to judge the annoyance of a particular signal presented at a constant level. Suppose further that the annoyance judgments are solicited on a five-category absolute judgment scale (e.g., “not at all annoying,” “slightly annoying,” “moderately annoying,” “very annoying,” and “extremely annoying”). If 200 of these 1,000 judgments fall in the categories “very” or “extremely” annoying, few would quibble with characterizing the probability as 0.2 that the signal when presented at the level in question would be judged “highly” (that is, either “very” or “extremely”) annoying.

The resulting dichotomy of annoyance judgments (“highly annoyed” versus “not highly annoyed”) seems consistent with Schultz's (1978) prevalence of annoyance scale. However, the prevalence ofhigh annoyance in a community is estimated from a count of the number of respondents expressing a shared opinion about the long-term annoyance of neighborhood noise exposure, not about the annoyance of individual noise intrusions. For example, if 40 of 200 survey respondents at an interview site with homogeneous noise exposure describe themselves as either “very” or “extremely” annoyed by neighborhood noise exposure, the proportion of highly annoyed respondents associated with the neighborhood noise exposure is said to be 0.2.

Both dichotomized annoyance judgments from controlled-exposure studies and annoyance prevalence estimates from social surveys may be treated as binomial proportions. Each person in a community is assumed to be either highly annoyed (p) or not highly annoyed (q = 1 − p) by each flyover. The expectation of the binomial distribution is simply Np, the product of the number of people exposed and the probability of high annoyance per flyover. Expectations of the prevalence of annoyance can then be based simply on total population.

Even though these binomial proportions can be manipulated in a similar manner, the two types of information on which they are based are not necessarily comparable. The binomial estimate of the prevalence of annoyance induced by a given noise intrusion cannot be directly interpreted as the long-term annoyance of repeated exposures.



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