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popper-logic-scientific-discovery

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436<br />

new appendices<br />

statements e, f, g, h, . . . which form the elements of S 2, some kind of<br />

frequency interpretation of probability. At the same time, we may assume the<br />

<strong>logic</strong>al interpretation of probability for the probability statements of the form<br />

P(g, h) = r<br />

that is to say, for the secondary probability statements which make<br />

assertions about the degree of probability of the primary probability<br />

statements, g and h.<br />

Although we may not have a <strong>logic</strong>al (or absolute) metric of the<br />

primary probability statements, that is to say, although we may have no<br />

idea of the value of p(a) or of p(b), we may have a <strong>logic</strong>al or absolute<br />

metric of the secondary probability statements: this is provided by the<br />

Laplacean distribution, according to which P(g), the absolute probability<br />

of g, that is to say of δ r (a) n, equals 2δ, whether g is empirically<br />

observed, or a hypothesis; so that the typical probabilistic hypothesis, h,<br />

gets P(h) = 0, because h has the form ‘p(a, b) = r’, with δ = 0. Since<br />

Bernoulli’s methods allow us to calculate the value of the relative probability<br />

P(g, h), by pure mathematical analysis, we may consider the<br />

relative probabilities P(g, h) as likewise determined on purely <strong>logic</strong>al<br />

grounds. It therefore seems entirely adequate to adopt, on the<br />

secondary level, the <strong>logic</strong>al interpretation of the formal calculus of<br />

probability.<br />

To sum up, we may consider the methods of Bernoulli and Laplace as<br />

directed towards the establishment of a purely <strong>logic</strong>al metric of probabilities<br />

on the secondary level, independently of whether or not there<br />

exists a <strong>logic</strong>al metric of probabilities on the primary level. Bernoulli’s<br />

methods determine thereby the <strong>logic</strong>al metric of relative probabilities<br />

(secondary likelihood of primary hypotheses, in the main), and<br />

Laplace’s the <strong>logic</strong>al metric of absolute probabilities (of statistical<br />

reports upon samples, in the main).<br />

Their efforts were, no doubt, directed to a large extent towards<br />

establishing a probabilistic theory of induction; they certainly tended<br />

to identify C with p. I need not say that I believe they were mistaken in<br />

this: statistical theories are, like all other theories, hypotheticodeductive.<br />

And statistical hypotheses are tested, like all other hypotheses,<br />

by attempts to falsify them—by attempts to reduce their secondary

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