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In probability theory, an outcome is a possible result of an experiment or trial. [1] Each possible outcome of a particular experiment is unique, and different outcomes are mutually exclusive (only one outcome will occur on each trial of the experiment).
The surgery had a known probability of success. Subjects were presented with either a good or bad outcome (in this case living or dying), and asked to rate the quality of the surgeon's pre-operation decision. Those presented with bad outcomes rated the decision worse than those who had good outcomes.
Normally a reduction in the probability of winning a reward (e.g., a reduction from 80% to 20% in the chance of winning a reward) creates a psychological effect such as displeasure to individuals, which leads to the perception of loss from the original probability thus favoring a risk-averse decision.
In probability theory, an experiment or trial (see below) is any procedure that can be infinitely repeated and has a well-defined set of possible outcomes, known as the sample space. [1] An experiment is said to be random if it has more than one possible outcome, and deterministic if it has only one.
The tendency to be over-optimistic, underestimating greatly the probability of undesirable outcomes and overestimating favorable and pleasing outcomes (see also wishful thinking, valence effect, positive outcome bias, and compare pessimism bias). [108] [109] Ostrich effect: Ignoring an obvious negative situation. Outcome bias
For example, individuals may unconsciously treat an outcome with a probability of 99% as if its probability were 95%, and an outcome with probability of 1% as if it had a probability of 5%. Under- and over-weighting of probabilities is importantly distinct from under- and over-estimating probabilities, a different type of cognitive bias ...
Experiment 3 studied negative outcomes and also found evidence of a weighting function that is more S-shaped for affect-rich than affect-poor prizes. Therefore, probability-outcome dependence based on the affect-rich psychology of risk applies in the domains of both gains and losses. [2]
In studies of the bias, options are presented in terms of the probability of either losses or gains. While differently expressed, the options described are in effect identical. Gain and loss are defined in the scenario as descriptions of outcomes, for example, lives lost or saved, patients treated or not treated, monetary gains or losses. [2]