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    If a variable set is causally sufficient, then the error ... — Carmelics
    Home/Causation
    HistoryEditSee Inverse

    If a variable set is causally sufficient, then the error variables for any two variables in that set are probabilistically independent.

    CausationTruth & Knowledge
    ?Rate how convincing each reason is below to see the overall strength.
    1 reason for
    2 reasons against

    Reasons For

    1 perspective
    Reason for
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    • 1.Causal sufficiency of the variable set implies that error variables U_X and U_Y are causally unrelated.
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    • 2.The Common Cause Principle holds that variables without a common cause or direct causal relationship are probabilistically independent.
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    Reasons Against

    2 perspectives
    Reason against 1 of 2
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    • 1.Causal sufficiency requires no unmeasured common causes, but latent variables can induce error correlations without being 'causes' in the system.
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    • 2.Spirtes, Glymour & Scheines acknowledge that cyclic causal structures can produce correlated errors even in causally sufficient sets.
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    • 3.Therefore, causal sufficiency as standardly defined does not guarantee probabilistic independence of error terms in non-acyclic models.
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    Reason against 2 of 2
    ?
    • 1.Cartwright argues that the Common Cause Principle fails in quantum entanglement cases, where correlated variables share no screener-off common cause.
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    • 2.If the CCP admits physically realized exceptions, probabilistic independence cannot be derived from mere absence of causal relations between error terms.
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    Related

    Cartwright argues that the Common Cause Principle fails in quantum entanglement ...Causal sufficiency of the variable set implies that error variables U_X and U_Y ...Causal sufficiency requires no unmeasured common causes, but latent variables ca...If the CCP admits physically realized exceptions, probabilistic independence can...
    +3 moreShow less
    Spirtes, Glymour & Scheines acknowledge that cyclic causal structures can produc...The Common Cause Principle holds that variables without a common cause or direct...Therefore, causal sufficiency as standardly defined does not guarantee probabili...

    Similar

    If a variable set is causally sufficient, then the error variables for...94%Causal sufficiency of the variable set implies that error variables U_...89%In a causally sufficient DAG, the error variables U_X and U_Y are not ...86%The Common Cause Principle holds that variables without a common cause...80%

    Source

    AI-extracted1/3 agreementValid
    SEP: physics-Rpcc
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    It is usually assumed that if a variable set is causally sufficient, then the error variables will be probabilistically independent, and the probability distribution over \(\mathbf{V}\) will satisfy the Causal Markov Condition with respect to the true causal graph. Note that this assumption is very similar to the Common Cause Principle itself. If X and Y are variables included in a causally sufficient DAG, and \(U_X\) and \(U_Y\) are their corresponding error variables, then neither \(U_X\) nor
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    Validity: Extracted via Max plan + API grounding/validity checks

    Details

    Type
    claim
    Perspectives
    3 (1 for, 2 against)
    Edits
    1 edit