Interpretations, assessing probability

When conducting a quantitative risk assessment the analyst(s) must define its probabilistic basis, and in most cases this means either to use the classical frequency approach or the Bayesian approach. The classical statistical approach is and has been the most commonly used probabilistic basis in health care (Schneider 2006). This approach interprets a probability as the relative fraction of times the event considered occurs if the situation analyzed were hypothetically repeated an infinite munber of times. The imder-lying probability is unknown, and is estimated in the risk analysis. In the alternative, the Bayesian perspective, a probability is a measure of imcertainty about future events and outcomes (consequences), as seen through the eyes ofthe assessor(s) and based on his/her backgroimd information and knowledge at the time of the analysis. Probability is a subjective measure of imcertainty. 

Interpreting PSA as any risk assessment using accident probabilities and consequences, government and industry have prepared many examples. These are discussed as Public Risk, Specialized Analyses, and Performance Improvement. 

If the probability distribution of the data is or assumed Gaussian, several statistical measures are available for interpreting the data. These measures can be used to interpret the latent variables determined by a selected data analysis method. Those described here are a combination of statistical measures and graphical analysis. Taken together they provide an assessment of the statistical significance of the analysis. 

The PAF indicates the likelihood that adverse ecological effects will occur as a result of TBT exposure in a particular area. This value can be interpreted as the probability that a randomly selected exposure concentration will exceed species sensitivity. The probabilistic risk assessment was performed on the clustered data for harbours and for open waters, as well as for each harbour and open water separately. Only water systems for which exposure concentrations were measured at two or more locations were selected (all open waters and 19 out of 30 harbours). 

The first problem in interpretation of the probable ecotoxicity of a given chemical is selecting those species and possible effects, which are most significant (Duffus, 1986). This requires a knowledge of ecosystems at risk together with an ability to assess the likely toxicity of the chemical from its chemical and physical properties and mammalian effect data that are usually available. 

The deviation scenarios found in the previous step of the risk analysis must be assessed in terms of risk, which consists of assigning a level of severity and probability of occurrence to each scenario. This assessment is qualitative or semi-quantitative, but rarely quantitative, since a quantitative assessment requires a statistical database on failure frequency, which is difficult to obtain for the fine chemicals industry with such a huge diversity of processes. The severity is clearly linked to the consequences of the scenario or to the extent of possible damage. It may be assessed using different points of view, such as the impact on humans, the environment, property, the business continuity, or the company s reputation. Table 1.4 gives an example of such a set of criteria. In order to allow for a correct assessment, it is essential to describe the scenarios with all their consequences. This is often a demanding task for the team, which must interpret the available data in order to work out the consequences of a scenario, together with its chain of events. 

The interpretation of the results of all trials requires the close collaboration of clinicians and statisticians. Reliable results are only obtained if at least the minimum number of patients for statistical viability are involved in the preliminary trials. It is often difficult to measure precisely the parameter chosen for assessment. Consequently, results are usually quoted in terms of a probability coefficient, the lower the value of this coefficient the more accurate the results. However, very reliable results will only be obtained from clinical trials if large groups of patients are tested. This is seldom feasible. Consequently, manufacturers and licencing authorities usually settle for the best statistical compromise. Since some adverse effects do not manifest themselves for years, it is necessary to constantly monitor the drug (Phase IV trials) after it has been released for general use. 

The suspicion that Schrodinger s interpretation of wave mechanics was suppressed and rejected by quantum physicists for non-scientific reasons, is inescapable. Because of this inherent bias the form of wave mechanics which became established as the basis of theoretical chemistry has, understandably, never been assessed independently for this purpose. The point electron that jumps between quantum states with statistical probability fails to explain chemical behaviour with the same authority that it enjoys in physics. Nevertheless, the Schrodinger alternative is dismissed out of hand by chemists. A typical expert on quantum chemistry declares [33] ... 

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