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Essentially, this is achieved by accommodating a `worst-case' dependence structure (which is close to independence for most practical purposes). But such an approach is conservative if dependence is actually positive. To give an extreme example, under perfect positive dependence, there is effectively only one test and thus, the FWER is uninflated.
Take the example of a teacher who is uncertain about the extent to which a given student (with a severe communication impairment) understands what is said to them. The principle holds that it is less dangerous to assume that the student understands everything that is said, and to be wrong about that, than to assume that the student understands ...
For a Type I error, it is shown as α (alpha) and is known as the size of the test and is 1 minus the specificity of the test. This quantity is sometimes referred to as the confidence of the test, or the level of significance (LOS) of the test. For a Type II error, it is shown as β (beta) and is 1 minus the power or 1 minus the sensitivity of ...
To reduce the probability of committing a type I error, making the alpha value more stringent is both simple and efficient. To decrease the probability of committing a type II error, which is closely associated with analyses' power, either increasing the test's sample size or relaxing the alpha level could increase the analyses' power.
In the context of knowledge management, the closed-world assumption is used in at least two situations: (1) when the knowledge base is known to be complete (e.g., a corporate database containing records for every employee), and (2) when the knowledge base is known to be incomplete but a "best" definite answer must be derived from incomplete information.
In practice the politics and theology of the day determined the result of the dispute, but the nature of the controversy was a clear example of how different bundles of (usually implicit) auxiliary assumptions could support mutually inconsistent hypotheses concerning a single theory. In terms of either version of the Duhem–Quine thesis it ...
For example, the decoy effect shows that inserting a $5 medium soda between a $3 small and $5.10 large can make customers perceive the large as a better deal (because it's "only 10 cents more than the medium"). Behavioral economics introduces models that weaken or remove many assumptions of consumer rationality, including IIA. This provides ...
A faulty generalization often follows the following format: The proportion Q of the sample has attribute A. Therefore, the proportion Q of the population has attribute A. Such a generalization proceeds from a premise about a sample (often unrepresentative or biased), to a conclusion about the population itself. [3]