Biased questions

Independence of analysts and analyses in one organization is a fundamental question. It is important to have, even for the most reliable methods, more than one analyst/laboratory involved to avoid possible analyst/laboratory-specific biases. Certification by a single laboratory, without confirmation by another laboratory or method is risky. Measurement by a single definitive method is usually performed by two or more analysts working independently to minimize possible biases. Frequently, an accurately characterized back-up method is employed to corroborate the data. Some agencies feel that a certification campaign should not be based on a single measirrement procedure and therefore do not normally certify values on the basis of a definitive method applied in one laboratory. 

The concern of the independence of analysts in one organization still remains a fundamental question. Again it is important to have more than one analyst/laboratory involved to avoid possible analyst-specific and laboratory-specific biases. The characterization should be corroborated by additional methods or laboratories to provide additional assurance that the data are correct. 

How to judge the relevance of these asphericities Are they really compatible with the data or are they simply the biased result of an ill-adapted model The best way to answer this question is to use this result as a prior probability for a new MaxEnt reconstruction. The map thus obtained, which is given in Figure 4, is striking the... 

There are some biases concerning the stated response to WTP questions. Some responses might be from yes-sayers to please the interviewer. Others might give protest zeros responses, if the respondent disagree with the conducted scenario. While yet others desire a warm-glow since the respondent has a moral satisfaction from the act [25]. 

Critics of the MZA data who argue that various forms of bias (placement, rearing by relatives rather than random placement, etc.) probably lead to serious overestimates of genetic influence seldom address both the MZA and URT data sets simultaneously (Dorfman, 1995 Fancher, 1995). Since URTs live in the same home and are matched on far more variables than MZA twins, the whole array of commonly cited biases in MZA studies is brought into question. I used to call this kind of selective reporting pseudo-analysis (Bouchard, 1982) until I discovered it already had a name. It is called the Neglected Aspect Fallacy (Castell, 1935) and it violates Carnap s Total Evidence Rule (1950). 

In a deposition by oral examination before trial, the witnesses the lawyer will be examining are normally hostile or adversary. In these situations inductive logic can be a powerful weapon which enables the lawyer to divine what kind of person the witness is, how he is likely to answer questions, what his biases are, and how the lawyer can strengthen his own case or weaken his opponent s through the examination of this witness. 

Many people wonder why laywers are often so prolix. Usually it is an attempt to be clear. It is quite common for a lawyer to restate a question together with the answer. It is not at all uncommon for a client to present a long involved set of facts on which he wants a yes or no answer only to get a good many pages of restatement of the facts before a conclusion is reached. This is necessary to ensure that the client and the lawyer are discussing exactly the same question. Closely related questions may have different answers, and the client may bias the question so as to receive the response he wants. In such biasing, the question can become sufficiently different that it does not fit the circumstances found later to exist. 

In this section we shall examine some problems in which cnmr and pnmr spectroscopy have been used to try to answer questions about charge distribution. The selection is, of course, biased, but 2m attempt has been made to choose examples which one might have expected to be simple, but which turn out, on further analysis, to be quite puzzling. 

The example we jnst looked at is called one-sample t-test. It compares the mean of analytical resnlts with a stated valne. This is a typical analytical question. The problem may be two-tailed as in onr example, where it doesn t matter, if the analytical valne is biased to the one or the other direction. Or the question conld be one-tailed, e.g. if we want to know whether the copper content analysed in an alloy is below the specificatioa... 

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