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Because not all voters are Twitter users, and because not all Twitter users are voters, there will be a misalignment between the target population and the sampling frame that could lead to biased survey results because the demographics and opinions of Twitter using voters might not be representative of the target population of voters. [4]
CEP is not a good measure of accuracy when this distribution behavior is not met. Munitions may also have larger standard deviation of range errors than the standard deviation of azimuth (deflection) errors, resulting in an elliptical confidence region. Munition samples may not be exactly on target, that is, the mean vector will not be (0,0).
When one's sexual arousal is based on imagining oneself in another physical form (such as an animal, an infant, or an amputee) the erotic target is said to be one's self, or erotic target identity inversion (ETII).
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. [1]
The sociology of scientific knowledge (SSK) is the study of science as a social activity, especially dealing with "the social conditions and effects of science, and with the social structures and processes of scientific activity." [1] The sociology of scientific ignorance (SSI) is complementary to the sociology of scientific knowledge.
The "exceptional case" explanation is created at the intersection of low controllability of act and internal locus of control. Using this mode of reasoning, an individual excludes the particular outgroup member from the outgroup.
In the fields of sociology and social psychology, a breaching experiment is an experiment that seeks to examine people's reactions to violations of commonly accepted social rules or norms. Breaching experiments are most commonly associated with ethnomethodology, and in particular the work of Harold Garfinkel.
Monte Carlo methods are widely used in various fields of science, engineering, and mathematics, such as physics, chemistry, biology, statistics, artificial intelligence, finance, and cryptography. They have also been applied to social sciences, such as sociology, psychology, and political science.