Prior odds — their meaning and significance

The concepts of ‘prior odds’, a.k.a., prior probabilities or simply priors, and ‘posterior odds’ come up in most discussions about the evaluation of evidence. The significance and meaning of both terms becomes clear when viewed in the context of a “Bayesian approach”, or the logical approach, to evidence evaluation. That approach has been discussed at length elsewhere and relates to the updating of one’s belief about events based upon new information. A key aspect is that some existing belief, encapsulated as the ‘prior odds’ of two competing possibilities or events, will be updated on the basis of new information, encapsulated in the ‘likelihood-ratio’1 (another term you will undoubtedly have seen), to produce some new belief, encapsulated as ‘posterior odds’ about those same competing possibilities.

But what precisely do these terms, ‘prior odds’ and ‘posterior odds’, mean and how do they relate to the work of a forensic examiner?
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Hilton and Mathematical Probability

In 1958 Ordway Hilton participated in Session #5 of the RCMP Seminar Series. His article was originally published in that series by the RCMP, and subsequently republished in 1995 in the International Journal of Forensic Document Examiners.1

The later republication included the following abstract:

In every handwriting identification we are dealing with the theory of probability. If an opinion is reached that two writings are by the same person, we are saying in effect that with the identification factors considered the likelihood of two different writers having this combination of writing characteristics in common is so remote that for all practical purposes it can be disregarded. Such an opinion is derived from our experience and is made without formal reference to any mathematical measure. However, the mathematician provides us with a means by which the likelihood of chance duplication can be measured. It is the purpose of this paper to explore the possibility of applying such mathematical measure to the handwriting identification problem to see how we might quantitatively measure the likelihood of chance duplication.

Hilton’s article was written in 8 main sections with references, and is followed by a discussion between seminar participants. Today’s review will discuss each section of the article in turn.
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2014 ASQDE-ASFDE Panel Discussion “Conclusions…”

The 2014 ASQDEASFDE conference included an interesting panel discussion with the title “Conclusions… Signature and Handwriting Conclusion Terminology and Scales”. I was fortunate to be able to take part, albeit only remotely via Skype.

ASQDE ASFDE logos

 

The abstract for the session was as follows:

A current and global issue in our field is the topic of conclusion terminology and conclusion scales, particularly in respect of signature and handwriting conclusions. It is an important yet difficult topic to address because, while there is some commonality in the conclusion scales used in different geographical regions around the world, within a number of geographical regions there are multiple scales in use. It is for this very reason that it is also a topic in great need of discussion and there is a strong argument that we should attempt to reach a consensus (even if the result is that we agree to disagree).

This panel discussion is a collaboration of insights from numerous colleagues in our field in person, via Skype and in writing from private and government laboratories in geographical regions across the Americas, Australia, Asia, Africa, the Middle East and Europe.
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ICFIS 2014 — Teaching the Logical Approach for Evidence Evaluation to FDEs

This year’s International Conference on Forensic Inference and Statistics (ICFIS) is being held at Leiden University in the Netherlands.  ICFIS 2014 logoICFIS conferences are always very good and this is the 9th such event.  I am hoping to attend to present my thoughts on the topic of education relating to the logical (a.k.a. likelihood-ratio or LR) approach to evidence evaluation. Over the last few years I have given several one and two-day seminars and workshops on this topic, mainly for Forensic Document Examiners (FDEs) though the subject matter relates to all disciplines equally.  Those workshops have been great and provided a relatively unusual opportunity to learn about how fully trained examiners come to grips with a complicated and difficult topic.  One that is fundamental to FDE work.
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ASQDE “Conclusions and Logical Inference” Workshop 2013

This year the Annual General Meeting of the American Society of Questioned Document Examiners (ASQDE) ASQDE 2013 is being held in Indianapolis, Indiana on August 24 through 29, 2013. In keeping with the theme, “Demonstrative Science: Illustrating Findings in Reports and Court Testimony”, I will be presenting a one-day workshop entitled “Conclusion Scales and Logical Inference” on Sunday, August 25.
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Introduction to the Logical Approach to Evidence Evaluation

Forensic scientists, individually and as a group, want to be completely logical, open and transparent in their approach to the evaluation of evidence. Such an assertion is unquestionable. Further, I am sure that most document examiners believe this is exactly what they are achieving when they apply the procedures outlined in various traditional textbooks or the SWGDOC/ ASTM standards; for example, the SWGDOC Standard for Examination of Handwritten Items. Given the very understandable desire to be logical, I find it strange that so many people have a negative attitude towards anything and everything “Bayesian” in nature. After all, a logical approach to evidence evaluation that conforms to the overall Bayesian philosophy or approach is, quite literally, the embodiment of logic (more specifically, probabilistic logic).

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Accuracy and precision

The terms accuracy and precision are often confused or misunderstood.  But every scientist, forensic or otherwise, should understand what they mean.  In simple terms, ‘accuracy’ relates to how closely the value comes to the real score or true value (being ‘on target’). ‘Precision’, on the other hand, relates to the consistency of the value in repeated testing.  Any given test, statistic or process may produce results that are one or the other, both or neither.

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