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Decision Making Under Uncertainty
Published in Charles Yoe, Principles of Risk Analysis, 2019
Figure 19.2 presents an evidence hierarchy. The predictive power of the decision increases as the supporting evidence moves up the hierarchy. Decision Innovations (http://www.decision-making-solutions.com) defines the evidence hierarchy categories as follows: Analogical evidence is a weak form of evidence that suggests something true about one thing is also true about another thing due to its similarity.Anecdotal evidence arises from small sample sizes that are frequently not representative of typical experience. Anecdotal evidence indicates possibility without establishing likelihood.Statistical evidence provides evidence of causality, but it does not prove causality. Statistical inference helps establish causal relationships.Facts represent verifiable actual occurrences. They include empirical and historical evidence as well as scientific facts that can be confirmed with repeatable experiments.
Decision making under uncertainty
Published in Charles Yoe, Primer on Risk Analysis, 2019
Figure 7.2 presents an evidence hierarchy. The predictive power of the decision increases as the supporting evidence moves up the hierarchy. Decision Innovations (https://www.decision-making-solutions.com) defines the evidence hierarchy categories as follows: Analogical evidence is a weak form of evidence that suggests something true about one thing is also true about another thing due to its similarity.Anecdotal evidence arises from small sample sizes that are frequently not representative of typical experience. Anecdotal evidence indicates possibility without establishing likelihood.Statistical evidence provides evidence of causality, but it does not prove causality. Statistical inference helps establish causal relationships.Facts represent verifiable actual occurrences. They include empirical and historical evidence as well as scientific facts that can be confirmed with repeatable experiments.
Be Alert for Unconscious Bias, Everyone Has It
Published in Joel D. Levitt, Leadership Skills for Maintenance Supervisors and Managers, 2020
An observer who only sees a selected data set may thus wrongly conclude that most, or even all, of the data are like that. Cherry-picking can also is part of other logical fallacies. For example, the “fallacy of anecdotal evidence” tends to overlook large amounts of data in favor of some other cause.
A review of historical earthquakes in Queensland utilising the Trove Newspaper Archive as a primary source
Published in Australian Journal of Earth Sciences, 2021
D. Rubenach, J. Daniell, P. Dirks, J. Wegner
There are issues with the reliability of anecdotal evidence (Cuthbertson & Brown, 2011; Everingham et al., 1982). For example, many Queenslanders were unfamiliar with earthquakes and confused them with a variety of phenomena such as burglars, animals, and weather events (Earth Tremor of the North, 1913; Earthquake in Queensland, 1913; Houses Shaken, 1928; Mareeba, 1928; The Earth Tremors, 1918a). Also, it is well known that many people unfamiliar with earthquakes tend to exaggerate the amount of shaking they felt (Everingham et al., 1982). Many earthquakes occurred at odd hours of the night or early morning and a person suddenly awoken may not be a reliable witness (Earth Tremor of the North, 1913; The Earthquake, 1883d). It is not unusual for significant numbers of people to sleep through all but the largest of earthquakes (Diamond, 2014; Earth Tremor of the North, 1913; Earthquake, 1918a; Miller, 2018). Despite these issues, by compiling many accounts of an earthquake, it is possible to estimate its epicentre location and magnitude, in the procedure applied here.
‘All theory is gray … but forever green is the tree of life’
Published in Policy and Practice in Health and Safety, 2019
The title of this editorial is taken from a well-known quote by the German poet and philosopher J.W. Goethe (1749–1832). Goethe was partly lamenting the amount of time other scientists and thinkers spend on matters which largely theoretical, in contrast to those who gather data or use their intuition and experience to drive their work. Within the context of Policy and Practice in Health and Safety (PPHS) the quote might at first appear to have little relevance, however one of the aims of PPHS is to act as a forum for the discussion of scientific and practice-based aspects of occupational health and safety. Part of this involves theory and theoretical matters as these often crop up in discussions of the relevance of one rival theory of health and safety over another (e.g. comparisons between High Reliability Organization Theory and Resilience Engineering and their applicability to safety critical contexts – e.g. Haavik, Antonsen, Rosness, & Hale, 2019; Harvey, Waterson, & Dainty, 2019; Behavioural safety and its influence on safety culture – e.g. Marsh, 2017). One of the key roles of theory is to generate predictions and to arrive at something (e.g. an intervention) which can be tested and verified. Without a sound and detailed theory (or a set of theories) research runs the risk of delivering only anecdotal evidence which in turn, is difficult to translate into practice. As Andrew Hale (2014) puts it: