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Unformatted text preview: ndence and approaches
to modelling dependence are given in Newendorp (1996 pp406-431), Goodwin and
Wright (1991 pp153-157), Eilon and Fawkes (1973) and Hull (1977). There is significant evidence in the prescriptive decision analysis literature that decisionmakers have difficulty assigning the strength of association between variables.
Nisbett and Ross (1980 p26) have given the following concise summary of this
“The evidence shows that people are poor at detecting many sources of
covariation … Perception of covariation in the social domain is largely a
function of pre-existing theories and only very secondarily a function of true
covariation. In the absence of theories, people’s covariation detection
capacities are extremely limited. Though the conditioning literature shows
that both animals and humans are extremely accurate covariation detectors
under some circumstances, these circumstances are very limited and
constrained. The existing literature provides no reason to believe that …
humans would be able to detect relatively weak covariations among stimuli
that are relatively indistinctive, subtle and irrelevant motivationally and, most
importantly, among stimuli when the presentation interval is very large.” 101 Chapman and Chapman’s 1969 study provided evidence of a phenomenon that they
refer to as illusory correlation. In their experiment, naïve judges were given information on several hypothetical mental patients. This information consisted of a
diagnosis and drawing made by the patient of a person. Later the judges were asked
to estimate how frequently certain characteristics referred to in the diagnosis, such as
suspiciousness, had been accompanied by features of the drawing, such as peculiar
eyes. It was found that judges significantly overestimated the frequency with which,
for example, suspiciousness and peculiar eyes occurred together. Moreover, this
illusory correlation survived even when contradictory evidence was presented to the
judges. Tversky and Kahneman (1974) have suggested that such biases are a consequence of the availability heuristic. It is easy to imagine a suspicious person
drawing an individual with peculiar eyes, and because of this, the real frequency with
which the factors co-occurred was grossly overestimated. So, in the case of the
relationship between porosity and water saturation, this research suggests that because
geologists expect there to be a correlation, if there is any evidence of a correlation in
any particular case, the geologist is likely to overestimate the strength of this
relationship. This research indicates the powerful and persistent influence that preconceived notions can have on judgements about relationships (Goodwin and
Wright, 1991 p153).
The third limitation of Monte Carlo simulations is perhaps most significant. In the
industry literature, no published study has indicated which probability distribution
most accurately describes the reservoir parameters of reservoir rocks of similar
lithology and water depth. Similarly, there has been no research that has identified
the appropriate shape of probability distribution to be adopte...
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This document was uploaded on 03/30/2014.
- Summer '14
- The Land