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The foundation of the uncertainty reduction theory stems from the information theory, originated by Claude E. Shannon and Warren Weaver. [2] Shannon and Weaver suggests, when people interact initially, uncertainties exist especially when the probability for alternatives in a situation is high and the probability of them occurring is equally high. [6]
Yet now is the time when we can least afford to retreat into fortress certainty and miss out on the unsung opportunities for growth and wisdom offered by being unsure.
Uncertainty management theory (UMT), developed by Dale Brashers, addresses the concept of uncertainty management. Several theories have been developed in an attempt to define uncertainty, identify its effects and establish strategies for managing it. [1] Uncertainty management theory was the first theory to decline the idea that uncertainty is ...
Predicted outcome value theory is an alternative to uncertainty reduction theory, which Charles R. Berger and Richard J. Calabrese introduced in 1975. Uncertainty reduction theory states that the driving force in initial interactions is to collect information to predict attitudes and behaviors for future relationship development.
Regret theory models choice under uncertainty taking into account the effect of anticipated regret. Subsequently, several other authors improved upon it. [4] It incorporates a regret term in the utility function which depends negatively on the realized outcome and positively on the best alternative outcome given the uncertainty resolution. This ...
The need for closure in social psychology is thought to be a fairly stable dispositional characteristic that can, nonetheless, be affected by situational factors. The Need for Closure Scale (NFCS) was developed by Arie Kruglanski, Donna Webster, and Adena Klem in 1993 and is designed to operationalize this construct and is presented as a unidimensional instrument possessing strong discriminant ...
In physical experiments uncertainty analysis, or experimental uncertainty assessment, deals with assessing the uncertainty in a measurement.An experiment designed to determine an effect, demonstrate a law, or estimate the numerical value of a physical variable will be affected by errors due to instrumentation, methodology, presence of confounding effects and so on.
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