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Expectancy–value theory has been developed in many different fields including education, health, communications, marketing and economics. Although the model differs in its meaning and implications for each field, the general idea is that there are expectations as well as values or beliefs that affect subsequent behavior.
The expectancy theory of motivation explains the behavioral process of why individuals choose one behavioral option over the other. This theory explains that individuals can be motivated towards goals if they believe that there is a positive correlation between efforts and performance, the outcome of a favorable performance will result in a desirable reward, a reward from a performance will ...
Any definition of expected value may be extended to define an expected value of a multidimensional random variable, i.e. a random vector X. It is defined component by component, as E[X] i = E[X i]. Similarly, one may define the expected value of a random matrix X with components X ij by E[X] ij = E[X ij].
A large majority of people prefer the sure thing over the gamble, although the gamble has higher (mathematical) expected value (also known as expectation). The expected value of a monetary gamble is a weighted average, in which each possible outcome is weighted by its probability of occurrence. The expected value of the gamble in this example ...
The expected value or mean of a random vector is a fixed vector [] whose elements are the expected values of the respective random variables. [ 3 ] : p.333 E [ X ] = ( E [ X 1 ] , . . .
A random variable is a measurable function: from a sample space as a set of possible outcomes to a measurable space.The technical axiomatic definition requires the sample space to be a sample space of a probability triple (,,) (see the measure-theoretic definition).
Experimenter's or expectation bias, the tendency for experimenters to believe, certify, and publish data that agree with their expectations for the outcome of an experiment, and to disbelieve, discard, or downgrade the corresponding weightings for data that appear to conflict with those expectations.
Second, it is also used to abbreviate "expect value", which is the expected number of times that one expects to obtain a test statistic at least as extreme as the one that was actually observed if one assumes that the null hypothesis is true. [49] This expect-value is the product of the number of tests and the p-value.