In qualitative terms, we start with a prior belief in the probability a hypothesis is true or false. ”Bayes Theorem” says that given new evidence (E), the updated (posterior) belief that a hypothesis is true (p(H|E) is a function of the conditional probability of observing the evidence given the hypothesis (p(E|H), times the prior probability that the hypothesis is true (p(H)), divided by the probability of observing the new evidence (p(E)). In the 18th century, Reverend Thomas Bayes invented a quantitative method for using new information to update a prior degree of belief in the truth of a hypothesis. We typically fill in these gaps with assumptions, about which we have varying degrees of uncertainty. Bacon believed the weight of evidence for or against a hypothesis depends on both how much relevant and credible evidence you have, and on how complete your evidence is with respect to matters which you believe are relevant to evaluating the hypothesis.īacon recognized that we can be “out on an evidential limb” if we draw conclusions about the probability a hypothesis is true based on our existing evidence without also taking into account the number relevant questions that are still not answered by the evidence in our possession. In the 17th century, Sir Francis Bacon developed a method for weighing evidence. There are three systematic approaches to weighing evidence in order to reach a conclusion. Probative Force or Weight: Is concerned with the incremental impact of a piece of evidence on the probabilities associated with one or more of the hypotheses under consideration.Believability: Is a function of the credibility and competence of the source of the evidence.Relevance: “Relevant evidence is evidence having any tendency to make more or less probable than it would be without the evidence” (from the US Federal Rules of Evidence).Regardless of its type, all evidence has three fundamental properties: Conflicting evidence supports different hypotheses, but the pieces of information are not mutually exclusive.Contradictory evidence is two or more pieces of information that are mutually exclusive, and cannot both or all be true.Convergent: Two or more sources provide information about different events, all of which support the same hypothesis.Corroborating: Two or more sources report same information, or one source reports the information and the other attests to the first’s credibility. Hence this short note, which will cover some basic aspects of evidence, and quickly review three approaches to weighing it.Įvidence has been defined as “any factual datum which in some manner assists in drawing conclusions, either favorable or unfavorable, retarding a hypothesis.”īroadly, there are at least four types of evidence: Unfortunately, it is one that too many schools fail to teach. In a radically uncertain world, the ability to systematically weigh evidence to reach a justifiable conclusion is undoubtedly a critical skill. With so many people and organizations facing this challenge today in our post-COVID world, we're publishing it here. In our course on Strategic Risk Governance and Management, we stress that skill in weighing evidence is one of the keys to making high quality decisions in the face of high uncertainty. We first published this post on Britten Coyne Partners blog back in April 2018.
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