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arxiv: 1003.3659 · v1 · submitted 2010-03-18 · 🧮 math.HO · math.PR· physics.data-an

On the Peirce's "balancing reasons rule" failure in his "large bag of beans" example

classification 🧮 math.HO math.PRphysics.data-an
keywords blackbeansrulebalancingequallylargemakepeirce
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Take a large bag of black and white beans, with all possible proportions considered initially equally likely, and imagine to make random extractions with reintroduction. Twenty consecutive observations of black make us highly confident that the next bean will be black too. On the contrary, the observation of 1010 black beans and 990 white ones leads us to judge the two possible outcomes about equally probable. According to C.S. Peirce this reasoning violates what he called "rule of balancing reasons", because the difference of "arguments" in favor and against the outcome of black is 20 in both cases. Why? (I.e. why does that rule not apply here?)

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