Scientific hypotheses testing

In the famous case Daubertv. MerrellDow, the Supreme Court held that expert testimony relating to scientific studies must be grounded in the methods of science. The basic test for any scientific hypothesis or model is to compare its predictions against observations. Hypothesis and models that make accurate predictions are accepted as useful and scientific, while those that fail to make adequate predictions are discarded or modified.2... 

This, in a nutshell, is what science is all about—it is a process by which new ideas are created to help explain what we observe in nature, both out-of-doors and in the laboratory. The new idea with its explanatory powers is called a hypothesis. The hypothesis is a scientific hypothesis when, and only when, it can be tested. The more tests that the scientific hypothesis passes, the greater the confidence we have that the hypothesis is true. However, if the hypothesis fails even one test, then the hypothesis is taken to be false. A new, more all-encompassing idea is needed. 

Scientific law Any scientific hypothesis that has been tested over and over again and has not been contradicted. Also known as a scientific principle. 

It helps us summarize and relate our observations, but it will probably not allow us to predict things we have not yet observed, if, however, we view the effects and their changes as manifestations or alterations in the subsystems and structures that make up the d-SoC, depth becomes a scientific hypothesis. We should then be able to predict things other than those we have measured and test these predi ctions.f11... 

Development of at least one scientific hypothesis and experimental methods to test hypothesis. 

Hypothesis testing is the basis for many decisions made in scientific and engineering work. To explain an observation, a hypothetical model is advanced and is tested experimentally to determine its validity. If the results from these experiments do not support the model, we reject it and seek a new hypothesis. If agreement is found, the hypothetical model serves as the basis for further experiments. When the hypothesis is supported by sufficient experimental data, it becomes recognized as a useful theory until such time as data are obtained that refute it. 

This brief excursion Into Decision Theory Is Included to Indicate the manner In which experimental data can be coupled with external (societal) judgments to form a logical basis for societal decisions and actions. A justification for so complex a strategy for decision making is that "simple scientific measurements and model evaluations will always be characterized by measurement uncertainty. Yet societal decisions and actions must take place even under the shadow of uncertainty. For scientific measurements, as discussed in Che following text, however, we shall restrict our attention to the relatively simple Neyman-Pearson hypothesis testing model (8, p. 198). 

In reviewing the history of detection limits (in Analytical Chemistry) it is helpful to keep these several, often implicit, differences in mind. If it Is agreed that the concept of detection has meaning, then it is essential that the above questions be fully defined and explicitly addressed. In the view of this author a meaningful approach to analyte detection must be consistent with our approach to uncertainty components of measurement processes and experimental results the soundest approach is probably the last [hypothesis testing] tempered with an appropriate measure of the first [scientific intuition]. 

Table I has been prepared from this perspective. The authors selected are drawn primarily from those who have contributed basic statements on the issue of detection capabilities of chemical measurement processes ["detection limits"], as opposed to simply addressing detection decisions for observed results ["critical levels"]. In fairness to those not listed, it is important to note that a) a selection only, spanning the last several decades has been given, and that b) there also exist many excellent articles (15.16) and books (12.17.18 > which review the topic. It is immediately clear from Table I that the terminology has been wide ranging, even in those cases where the conceptual basis (hypothesis testing) has been Identical. Nomenclature, unlike scientific facts and concepts, can be approached, however, through consensus. The International Union of Pure and Applied Chemistry [lUPAC], which appears twice in Table I, is the international body of chemists charged with this responsibility. At this point it will be helpful to examine the position of lUPAC as well as the contributions of some of the other authors cited in Table I.

Hypotheses have always been important in biology, as in the rest of science. The scientific method is based upon the cycle of hypothesis-test-hypothesis-test, and hypotheses made, whether proved true or false, indicate a state of knowledge somewhat above complete ignorance. 

Therefore, since language is so important, contextnal care mnst be taken to correctly understand the notions that figure in Popper s langnage. For example, mnch has been written in the recent systematics literature on a formalism that Popper nsed to characterize the degree of corroboration (C) of a scientific hypothesis, which increases with severity of test. Thns,... 

---