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2010-12-16 19:38:07

Phi Final
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  1. Causal Statement
    • a statement that asserts or denies that one thing or type of things causes another
    • "A causes B'
    • two kinds: specific and general
  2. Casual Argument
    an argument in which at least one causal statement occurs either as a premise or as a conclusion
  3. casual conclusion
    • an argument consisting of premises in support of a casual argument
    • strong if its premises have evidence from one or more of mill's methods
  4. specific causal statment
    • A causes B
    • that some specific thing caused or is caused by some other specific thing
  5. causal generalizations
    • asserts or denies a causal relationship btw types of things or events
    • -As cause Bs
  6. sufficient condition
    • the presence of this condition alone is capable of bringing about the effect
    • sufficient but not necessary; dont necessarily occur
    • A is a sufficient condition for B if and only if given that A occurs, B occurs. If B does not occur, then A has not occured
  7. necessary condition
    • the prescence of this condition must exist for effect to occur at all
    • the presence of necessary conditon does not entail the causal event will take place
    • A is necessary condition for B. If A doesnt not occur B does not occur
  8. necessary and sufficient conditions
    • <->
    • a certain condition, itself, is capable of bringing about the effect AND another condition must exist for the first condition to occur at all
    • A is necessary and sufficient for B if and only if given that A occurs, the B occurs and give than B occurs then A occurs.
  9. Partial Conditions
    A is a partial cause of B if and only if given factors f,g,h, the occurrence of A increases the likelihood of B, and A is neither sufficient nor necessary for B
  10. causal predictions
    • an argument consisting of a causal generalization
    • instance of a causal circumstance, and concluding that a specific effect occurs
    • we can predict what will occur if the cause is present
  11. causal explanations
    • an argument consisting of a causal generalization
    • an instance of an effect, and concluding that an instance of a specific cause explains the occurrence of the effect
    • give the causal statemtn of the first premise-which tells us how two events are related-we can explain that one event occurs because it isthe effect of another
    • 2 premises: generalization and consequent condition explanation
  12. causal prescriptions
    • an argument consisting of a causal generalzation
    • concluding with a prescription of recommendation for producing or preventing some effect
    • an arugment asserting how somethings is to be achieved, Given the casual statement as a premise, we know that if we want a certain result, then we need to bring about the case
  13. casual conclusions
    • an argument consisting of premises in support of a causal statement
    • Premises: data expresses relation btw events; detain assertion
    • Conclusion: casual statementl establishes that relation is causal
    • provides evidence for concluding that one things causes another
  14. Mill's Methods
    • used to evaluate casual conclusions
    • Agreement, Difference, Concomitant Variation, Residue
  15. Argument Method
    • If two or more instances of a phenomenon E have only one antecendent circumstance in common, then probably that antecedent circumstance is the cause or a partial cause of E
    • if a circumstance f is the only circumstance always present whenever E occurs, then we have supporting evidence for the conclusion that f is the cause of E
    • mill's first method for identifying a cause tells us to look for an antecedent circumstance present in all those case in which the phenonmeon occurs
  16. Difference Method
    • If an instance of a phenomenon E and an instance in which E does not occur differ only in the presence of one antecent circumstance with the instance of E, then that antecedent circumstance is probably the causes or partial cause of E
    • we compare cases in which the phenonomenon occurs with those cases in which it does not occur to discover in what way they differ
    • we look for some difference btw instances of a phenonmeon and instances without the phenonmenon fails to occur
  17. Concomitant Variation Method
    • If variations in phenomenon E coincides with variations in phenomenon P, then it i probable that E and P are causally related
    • given two phenomena that vary consistently, if one precedes the other, then we have supporting evidence that the former causes the latter
    • given two pehenomena that vary consistently, if by altering one we can produce concomitant variations in the other, then we have supporting evidence that the former causes the latter
    • useful in cases where we cannot take away a variable but only gives up correlations and evidence of connections. We need evidence that perhaps is provided by other methods
  18. Residue Method
    • substract from any phenomenon such part as is know by previous inductions to be the effect of certain antecedents, and the residue of the phenomenon is the effect of the remaining antecedents
    • if one or more parts can be casually explained by one or more parts of the antecedent circumstances, then we have supporting evidence that the remaining part of the phenomenon can be causally explained by the remaining antecedent circumstance
    • the method of residue presupposes some causal knowledge of a phenomenon; we have a partial understanding of the phenonmenon
    • this method allows us to identify at least one,perhaps other causal factors contributing to the phenonmeon

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