Search results
Results from the WOW.Com Content Network
Risk is the lack of certainty about the outcome of making a particular choice. Statistically, the level of downside risk can be calculated as the product of the probability that harm occurs (e.g., that an accident happens) multiplied by the severity of that harm (i.e., the average amount of harm or more conservatively the maximum credible amount of harm).
ISO 31000 is a set of international standards for risk management.It was developed in November 2009 by International Organization for Standardization. [1] The goal of these standards is to provide a consistent vocabulary and methodology for assessing and managing risk, resolving the historic ambiguities and differences in the ways risk are described.
ERM can also be described as a risk-based approach to managing an enterprise, integrating concepts of internal control, the Sarbanes–Oxley Act, data protection and strategic planning. ERM is evolving to address the needs of various stakeholders, who want to understand the broad spectrum of risks facing complex organizations to ensure they are ...
Relative risk is commonly used to present the results of randomized controlled trials. [5] This can be problematic if the relative risk is presented without the absolute measures, such as absolute risk, or risk difference. [6]
Risk management is the identification, evaluation, and prioritization of risks, [1] followed by the minimization, monitoring, and control of the impact or probability of those risks occurring. [2]
Absolute risk (or AR) is the probability or chance of an event.It is usually used for the number of events (such as a disease) that occurred in a group, divided by the number of people in that group.
Formally, a "database" refers to a set of related data accessed through the use of a "database management system" (DBMS), which is an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data).
The concept of data type is similar to the concept of level of measurement, but more specific. For example, count data requires a different distribution (e.g. a Poisson distribution or binomial distribution) than non-negative real-valued data require, but both fall under the same level of measurement (a ratio scale).