Comparing and contrasting the reality of subjectivity in the work of history's great scientists and the modern Bayesian approach to statistical analysis.
Weatherson B., Begging the question and Bayesians, , 30(4), 687-697, 1999.
The problem with the Classical Approach is that what constitutes an outcome is not objectively determined.
If there is a good argument to be constructed here, how are we to do it? First we have to recognize that there are different types of arguments. Some arguments are so structured that the truth of the premises (the assumptions) guarantees the truth of the claim being defended. In such , the claim follows from the assumptions. But there are many good arguments that do not have this characteristic. In fact, most of the arguments given to support scientific claims -- even the really good arguments -- do not have this property. This is because most scientists offer arguments in which the claim being considered is supported by evidence that makes the claim probable (often probable) but that does not logically guarantee the claim. We call arguments of this kind . Because science is concerned with learning contingent facts about the world that can never be to be true, the strongest support that can ever be offered for these claims is the that comes from inductive arguments. If we eliminate evidence statements 1-3, the resulting argument no longer begs the question. Moreover, it captures the rationale for believing that the positive data (evidence statement 2) verifies the hypothesis:
One may use this measure as a decision-making tool: This interpretation is widely accepted, and many scientific journals routinely publish papers using this interpretation for the result of test of hypothesis.
From the cybernetic perspective, threats cannot be welcomed and transcended a fortiori. They must be absorbed, eliminated. I’ve already said that the infinitely renewed impossibility of this annihilation of events is the final certainty that practices of opposition to the device-governed world can be founded on. Threat, and its generalization in the form of panic, poses an unsolvable energetic problem for the holders of the cybernetic hypothesis. Simondon thus explains that machines with a high information outflow and control their environment with precision have a weak energetic output. Conversely, machines that require little energy to carry out their cybernetic mission produce a poor rendering of reality. The transformation of forms into information basically contains two opposing imperatives: “information is in one sense that which brings a series of unpredictable, new states, following no predefined course at all; it is thus that which requires absolute availability from an information channel with respect to all the aspects of modulation that it routes along; the information channel should in itself have no predetermined form and should not be selective... On the opposite hand, information is distinct from noise because information can be assigned a certain code and given a relative uniformization; in all cases where noise cannot be immediately/directly brought down to below a certain level, a reduction of the margin of indetermination and unpredictability in information signals is made.” In other words, for a physical, biological, or social system to have enough energy to ensure its reproduction, its control devices must carve into the mass of the unknown, and slice into the ensemble of possibilities between what is characterized by pure chance, and has nothing to do with control, and what can enter into control as hazard risks, immediately susceptible to a probability calculation. It follows that for any device, as in the specific case of sound recording devices, “a compromise should be made that preserves a sufficient information output to meet practical needs, and an energy output high enough to keep the background noise at a level that does not disturb the signal levels.” Or take the case of the police as another example; for it, this would just be a matter of finding the balance point between repression — the function of which is to decrease social background noise — and reconnaissance/intelligence — which inform them about the state of and movements in society by looking at the signals it gives off.
The following table provides a reasonable interpretation of P-values: This interpretation is widely accepted, and many scientific journals routinely publish papers using this interpretation for the result of test of hypothesis.
In a collective scientific study, this would be somewhat more complex than for Frequentist hypotheses because priors must be personal for coherence to hold.
It is often said that (seeing what should have been observed) the hypothesis, showing that it is true. Hence, a test with positive data (evidence statement 5) results in this argument:
So, if our test results were negative, it follows that either the patient is not pregnant or one of our other assumptions is false ("dubious"). Which is more reasonable to believe? As is the case with most empirical research, it is usually the hypothesis that is less well accepted than the methodological, theoretical, and other auxillary assumptions. Thus, a negative test usually results in a hypothesis being abandoned or revised. And since the empirical question motivating the research has not been resolved, negative tests lead to further research. For that reason, negative data is not a "bad" thing. Besides, it is the scientist's job to discover truths about the world, not to defend a pet hypothesis against unfavorable evidence. Indeed! Where it is not possible to test an hypothesis (or theory), it is not possible to falsify it. Hypotheses (or theories) that are "true" no matter what can be observed in the world are not scientific (e.g., astrology). Rather, such hypotheses (or theories) are . Pseudoscience is always "bad" science.
But take a closer look at this argument. Does anything strike you as suspicious? Hopefully so, namely, that the first evidence statement and the claim are one and the same statement. Do you see this? It may help to note that while the expression 'let's assume that' make the first and last statements different, what each of those sentences asserts is one and the same statement -- H. Whenever something like this occurs, the argument is said to be (or beg the question). Because it is logically impermissible to presuppose the truth of your claim among your evidence when you are trying to show that your claim is true, every circular argument is a bad argument. But since it is impossible for the evidence to be true and for the claim to be false, owing to its circularity, every circular argument is a valid argument. However, we know this before we even perform the test. We can simply ignore statements 4 and 5 because the claim follows directly from statement 1 (as well as statement 3). And as the observed "data" is logically to the truth of the claim, it makes no sense to say that the observation the hypothesis.
It is often said that ( seeing what should have been observed) the hypothesis. But that is not necessarily true. What does logically follow from negative data is H and are not both true. In other words, either the hypothesis is false at least one member of the set of auxiliary assumptions is false. A test with negative data (evidence statement 5) results in the following argument:
Empirically speaking, whether what should have been observed was observed is the crucial piece of evidence that bears upon whether the hypothesis is true. As noted above, there are two possibilities. One is (because what was observed was what have been observed). The other is (because what should have been observed was observed). Logically speaking, things are not quite so simple. Let's deal with the easiest case first.
20. HYPOTHESIS CONTRARY TO FACT: This fallacy consists of offering a poorlysupported claim about what might have happened in the past or future if circumstances orconditions were other than they actually were or are. The fallacy also involves treatinghypothetical situations as if they were fact.example: Husband to ex-wife: Well, if you want to be completely fair about dividing everything up, you should get one of my testicles and I should get one of your breasts! example: Debtor to creditor: Hey, you've already repossessed my car and my television. Why don't you just draw a quart of blood or carve a pound of flesh from my heart too?