Answers.Body: <p>That term exactly refers to the difference between two main paradigms in probability and statistics: <a href="https://en.wikipedia.org/wiki/Frequentist_inference" rel="nofollow noreferrer">Frequentism</a> vs <a href="https://en.wikipedia.org/wiki/Bayesian_probability" rel="nofollow noreferrer">Bayesianism</a>. You can find many texts for explaining the difference, for example <a href="https://stats.stackexchange.com/a/56/144441">[1]</a> and <a href="https://cxl.com/blog/bayesian-frequentist-ab-testing/#:%7E:text=In%20summary%2C%20the%20difference%20is,without%20being%20assigned%20a%20probability." rel="nofollow noreferrer">[2]</a>.</p>
  <p>By the way, we can briefly say it means that we assume that there exists a fixed opinion out there (like a parameter of a distribution function) and we are going to estimate it based on the observation. Despite the Baysian probability, in frequentist probability, we assume that the opinion is not fixed and changing randomly based on observations.</p>
  
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Body: <p>In <a href="https://books.google.de/books?id=FtnyCAAAQBAJ&amp;pg=PA503&amp;lpg=PA503&amp;dq=Orderly+bayesian+meaning&amp;source=bl&amp;ots=FEb__hOhZ7&amp;sig=ACfU3U2xKmxm4Spx-CgWiy2m39GNPq39Dw&amp;hl=de&amp;sa=X&amp;ved=2ahUKEwiJ4pOu-cHzAhULqaQKHY50ASYQ6AF6BAg0EAM#v=snippet&amp;q=orderly&amp;f=false" rel="nofollow noreferrer">this page</a>, it's written (emphasis mine)</p>
  <blockquote>
  <p>If probabilities are thought to describe <strong>orderly opinions</strong>, Bayes theorem describes how the opinions should be updated in the light of new information</p>
  </blockquote>
  <p>What is your understanding/definition of &quot;orderly&quot; opinion?</p>
  <p>Maybe something like: a probability that is not arbitrarily chosen but well-founded and explainable?</p>
  
Tags: <terminology><books><bayes-theorem><probability-theory>
Title: What do we mean by "orderly opinions" in this sentence in the context of Bayes theorem?
UserDisplayName: MC5321
ThreadText: # What do we mean by "orderly opinions" in this sentence in the context of Bayes theorem?
  
  (Asked by: username_0 on 2021-10-11)
  
  In [this page](https://books.google.de/books?id=FtnyCAAAQBAJ&pg=PA503&lpg=PA503&dq=Orderly+bayesian+meaning&source=bl&ots=FEb__hOhZ7&sig=ACfU3U2xKmxm4Spx-CgWiy2m39GNPq39Dw&hl=de&sa=X&ved=2ahUKEwiJ4pOu-cHzAhULqaQKHY50ASYQ6AF6BAg0EAM#v=snippet&q=orderly&f=false), it's written (emphasis mine)
  
  > If probabilities are thought to describe **orderly opinions**, Bayes theorem describes how the opinions should be updated in the light of new information
  
  What is your understanding/definition of "orderly" opinion?
  
  Maybe something like: a probability that is not arbitrarily chosen but well-founded and explainable?
  
  **Tags:** terminology, books, bayes-theorem, probability-theory
  
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  ## 1 answers
  
  ### Answer by username_1 on 2021-10-11. Score: 1
  
  That term exactly refers to the difference between two main paradigms in probability and statistics: [Frequentism](https://en.wikipedia.org/wiki/Frequentist_inference) vs [Bayesianism](https://en.wikipedia.org/wiki/Bayesian_probability). You can find many texts for explaining the difference, for example [[1]](https://stats.stackexchange.com/a/56/144441) and [[2]](https://cxl.com/blog/bayesian-frequentist-ab-testing/#:%7E:text=In%20summary%2C%20the%20difference%20is,without%20being%20assigned%20a%20probability.).
  
  By the way, we can briefly say it means that we assume that there exists a fixed opinion out there (like a parameter of a distribution function) and we are going to estimate it based on the observation. Despite the Baysian probability, in frequentist probability, we assume that the opinion is not fixed and changing randomly based on observations.
  
  
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