*Paul F. A. Bartha*

- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195325539
- eISBN:
- 9780199776313
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195325539.003.0002
- Subject:
- Philosophy, Logic/Philosophy of Mathematics

This chapter discusses attempts by Aristotle, Hesse, Mill and others to deal with two problems: (1) finding criteria for evaluating analogical arguments, and (2) providing some form of philosophical ...
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This chapter discusses attempts by Aristotle, Hesse, Mill and others to deal with two problems: (1) finding criteria for evaluating analogical arguments, and (2) providing some form of philosophical justification. As regards the first problem, we can identify a valuable “commonsense” model in Hesse's work, though one that is capable of refinement. As regards the second problem, it is argued that most analyses to date have unsuccessfully cast the analogical argument as an incomplete form of deductive argument, as some type of sampling argument, or as induction by enumeration. Agassi's skeptical rejection of all analogical reasoning is criticized because it too misrepresents the logical structure of the argument form.Less

This chapter discusses attempts by Aristotle, Hesse, Mill and others to deal with two problems: (1) finding criteria for evaluating analogical arguments, and (2) providing some form of philosophical justification. As regards the first problem, we can identify a valuable “commonsense” model in Hesse's work, though one that is capable of refinement. As regards the second problem, it is argued that most analyses to date have unsuccessfully cast the analogical argument as an incomplete form of deductive argument, as some type of sampling argument, or as induction by enumeration. Agassi's skeptical rejection of all analogical reasoning is criticized because it too misrepresents the logical structure of the argument form.

*John L. Pollock*

- Published in print:
- 1990
- Published Online:
- November 2020
- ISBN:
- 9780195060133
- eISBN:
- 9780197560129
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780195060133.003.0009
- Subject:
- Computer Science, Artificial Intelligence, Machine Learning

The objective of this book is to provide an analysis of nomic probability in terms of its conceptual role. This requires an account both of what inferences ...
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The objective of this book is to provide an analysis of nomic probability in terms of its conceptual role. This requires an account both of what inferences can be drawn from nomic probabilities, and how nomic probabilities can be evaluated on the basis of nonprobabilistic information. We have an account of. That consists of the acceptance rules and the theory of direct inference. The theory of nonclassical direct inference also provides a partial account of. Some nomic probabilities can be evaluated in terms of others by using nonclassical direct inference. But in order to get this process started in the first place, there must be some other way of evaluating nomic probabilities that does not require any prior contingent knowledge of the values of such probabilities. It seems intuitively clear that that is accomplished by some kind of statistical induction. In statistical induction, we observe a sample of B’s, determine the relative frequency of A’s in that sample, and then estimate prob(A/B) to be approximately equal to that relative frequency. A close kin to statistical induction is enumerative induction, wherein it is observed that all of the B’s in the sample are A’s, and it is concluded that any A would be a B, that is, A ⇒ B. There are two possibilities regarding statistical and enumerative induction. They could be derivable from more basic epistemic principles, or they might be irreducible constituents of the conceptual role of nomic probability and nomic generalizations. These two possibilities reflect what have come to be regarded as two different problems of induction. The traditional problem of induction was that of justifying induction. But most contemporary philosophers have forsaken that for Goodman’s “new riddle of induction”, which I am construing here as the problem of giving an accurate account of correct principles of induction. This change in orientation reflects the view that principles of induction are basic epistemic principles, partly constitutive of rationality, and not reducible to or justifiable on the basis of anything more fundamental. I endorsed the latter view in my [1974], but now I am convinced that it is false.
Less

The objective of this book is to provide an analysis of nomic probability in terms of its conceptual role. This requires an account both of what inferences can be drawn from nomic probabilities, and how nomic probabilities can be evaluated on the basis of nonprobabilistic information. We have an account of. That consists of the acceptance rules and the theory of direct inference. The theory of nonclassical direct inference also provides a partial account of. Some nomic probabilities can be evaluated in terms of others by using nonclassical direct inference. But in order to get this process started in the first place, there must be some other way of evaluating nomic probabilities that does not require any prior contingent knowledge of the values of such probabilities. It seems intuitively clear that that is accomplished by some kind of statistical induction. In statistical induction, we observe a sample of B’s, determine the relative frequency of A’s in that sample, and then estimate prob(A/B) to be approximately equal to that relative frequency. A close kin to statistical induction is enumerative induction, wherein it is observed that all of the B’s in the sample are A’s, and it is concluded that any A would be a B, that is, A ⇒ B. There are two possibilities regarding statistical and enumerative induction. They could be derivable from more basic epistemic principles, or they might be irreducible constituents of the conceptual role of nomic probability and nomic generalizations. These two possibilities reflect what have come to be regarded as two different problems of induction. The traditional problem of induction was that of justifying induction. But most contemporary philosophers have forsaken that for Goodman’s “new riddle of induction”, which I am construing here as the problem of giving an accurate account of correct principles of induction. This change in orientation reflects the view that principles of induction are basic epistemic principles, partly constitutive of rationality, and not reducible to or justifiable on the basis of anything more fundamental. I endorsed the latter view in my [1974], but now I am convinced that it is false.

*Ruth Weintraub*

- Published in print:
- 2017
- Published Online:
- January 2018
- ISBN:
- 9780198746904
- eISBN:
- 9780191809125
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198746904.003.0012
- Subject:
- Philosophy, Philosophy of Science, Metaphysics/Epistemology

Scepticism about inference to the best explanation is far less often discussed than scepticism about another ampliative form of inference, enumerative induction. Both of these inference forms are ...
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Scepticism about inference to the best explanation is far less often discussed than scepticism about another ampliative form of inference, enumerative induction. Both of these inference forms are widely used, and scepticism about either can pose an important challenge. This chapter aims to redress the imbalance by giving scepticism about inference to the best explanation the attention it, too, deserves. The chapter’s conclusion is that inference to the best explanation, even to the observable, may be in a worse epistemic position than enumerative induction. The reason for this is that there are sceptical arguments that target inference to the best explanation which do not have inductive analogues, but the converse is not true.Less

Scepticism about inference to the best explanation is far less often discussed than scepticism about another ampliative form of inference, enumerative induction. Both of these inference forms are widely used, and scepticism about either can pose an important challenge. This chapter aims to redress the imbalance by giving scepticism about inference to the best explanation the attention it, too, deserves. The chapter’s conclusion is that inference to the best explanation, even to the observable, may be in a worse epistemic position than enumerative induction. The reason for this is that there are sceptical arguments that target inference to the best explanation which do not have inductive analogues, but the converse is not true.