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Objective Bayesianism and causal modelling in the social sciences Federica Russo Philosophy, Louvain & Kent
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Probabilistic causal claims ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Probabilistic causal claims ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Interpreting probability: a rush course ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Interpreting probability: a rush course ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Interpreting probability: a rush critique ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Bayesian interpretations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Bayesian interpretations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Bayesianism  empirically-based or objective  is the interpretation that best fit CM
Janus-faced probability ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Frequency-driven epistemic probabilities ,[object Object],[object Object],[object Object],[object Object],[object Object]
Credence-driven objective probabilities ,[object Object],[object Object]
The Janus you choose makes the whole difference ,[object Object],[object Object]
In fact: ,[object Object],[object Object],[object Object],Additionally: In the single-case the goal is not to claim credence about chance but  to express a rational degree of belief in an individual hypothesis
The case against? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The full-blown advantage of  objective Bayesianism ,[object Object],[object Object]
Hypothesis testing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Probability in hypothesis testing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Consider: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What’s the  probability of a hypothesis? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
…  the probability of  which  hypothesis? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
A problem of error? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
But what about the probability of the  Alternative  hypothesis? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Probability is the very guide of life ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Individual decisions ,[object Object],[object Object],[object Object],[object Object]
Decisions in policy making ,[object Object],[object Object],[object Object],[object Object]
To sum up and conclude ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Russo Vub Seminar

  • 1. Objective Bayesianism and causal modelling in the social sciences Federica Russo Philosophy, Louvain & Kent
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  • 10. Bayesianism  empirically-based or objective  is the interpretation that best fit CM
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Notes de l'éditeur

  1. For instance, if A is the proposition that a coin tossed at time t will fall heads, X is the proposition that the chance of A at time t is x , and E is the available evidence that does not contradict X ; the Principal Principle then says that x equals the actual degree of belief that the coin falls heads, conditionally on the proposition that its chance of falling heads is x . In other words, the chance of A equals the degree to which an agent believes in A .
  2. In fully personalistic approaches coherence is nec and suff for assignments of prior proba. So, the objection: aren’t frequencies just a pedagogical need? Carnap gives an interesting answer (Philosophical Foundations of Probability, §50-51, 41C). 1. we can do without frequencies if inductive logic is accepted. Reason 1: prob1 (subj) can be explicated as estimate of proba2 (obj). So, if proba2 is know, then proba1 just equals this value. Reason 2: even if proba2 is unknown, we can still compute proba1 as estimate of the unknown proba2 from *frequencies* in the sample But the subjectivist can still play a last card: the exchangeability argument. Briefly and informally, De Finetti shows that different agents may start with different prior probabilities, but, as evidence accumulates, their posterior proba will tend to converge, thus giving the illusory impression that objective probability exists.