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Doctrine of Chances

Doctrine of Chances is a United States Federal legal concept based on the premise that the probability of a recurrence of events with the same or similar circumstances pointing to a specific individual is not merely an accident.  The greater the number of similar occurrences pointing to that central figure, the stronger the probability that they occurred by design, not by chance.[1] 

The legal Doctrine is the basis for the investigations in the Posts of TheOdds.website.  What is the improbability of mere chance that the confluence of events at a single point in history surrounding the appearance of Jesus of Nazareth coincided with the many messianic prophecies and circumstances over the previous 2000-year timeline?

 

REFERENCES:

[1] “Rule 404.  Character Evidence; Crimes or Other Acts.”  Federal Rules of Evidence. Rule 404 (b) (1) and (b) (2). Cornell University Law School.  <http://www.law.cornell.edu/rules/fre/rule_404>.  

Sullivan, Sean P. “Probative Inference from Phenomenal Coincidence – Demystifying the Doctrine of Chances”.  University of Virginia, 17 May 2013, <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2389682>. 

“Doctrine of Chances.”  Academic.  Academic Dictionaries and Encyclopedias.  2013.  <http://en.academic.ru/dic.nsf/cide/52694/doctrine>.

Challenge the Facts

 

3 Questions to ask when weighing facts:

Should we believe it?

Is there evidence to support it?

How good is the evidence?

 

Data Science is an emerging science where the focus is placed on asking questions to challenge assumptions.and presumed facts.

Evidence is information that can be used to prove a fact, yet evidence should not be used just to prove or disprove a fact.

Facts are not always chiseled in marble – ask questions. If there is no evidence at all, then the statement is no more than an untested assumption.

Intuition and experience can be some of the strongest evidence. Examples are expert opinions, analogies, and research studies. Explore it – what does the evidence really say?

ATTRIBUTION:

Rose, Doug. “Learning Data Science: Ask Great Questions.” LinkedIN.com. 2017. Training video. <https://www.linkedin.com/learning/learning-data-science-ask-great-questions/challenge-evidence?u=2130250>.