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Accounting research is carried out both by academic researchers and by practicing accountants.Academic accounting research addresses all areas of the accounting profession, and examines issues using the scientific method; it uses evidence from a wide variety of sources, including financial information, experiments, computer simulations, interviews, surveys, historical records, and ethnography.
The importance of understanding and managing uncertainty in model results has inspired many scientists from different research centers all over the world to take a close interest in this subject. National and international agencies involved in impact assessment studies have included sections devoted to sensitivity analysis in their guidelines.
During the past two decades, researchers have conducted a large number of empirical studies related to financial constraints, and the measurements they use have generated controversy, Fazari et al. (1987) in their seminal work, find a positive relationship between resources available for investment and cash flow. [21]
Info-gap decision theory seeks to optimize robustness to failure under severe uncertainty, [1] [2] in particular applying sensitivity analysis of the stability radius type [3] to perturbations in the value of a given estimate of the parameter of interest.
Statistical conclusion validity is the degree to which conclusions about the relationship among variables based on the data are correct or "reasonable". This began as being solely about whether the statistical conclusion about the relationship of the variables was correct, but now there is a movement towards moving to "reasonable" conclusions that use: quantitative, statistical, and ...
Much research has been done to solve uncertainty quantification problems, though a majority of them deal with uncertainty propagation. During the past one to two decades, a number of approaches for inverse uncertainty quantification problems have also been developed and have proved to be useful for most small- to medium-scale problems.
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.
In economics, Knightian uncertainty is a lack of any quantifiable knowledge about some possible occurrence, as opposed to the presence of quantifiable risk (e.g., that in statistical noise or a parameter's confidence interval). The concept acknowledges some fundamental degree of ignorance, a limit to knowledge, and an essential unpredictability ...