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A Random Variable is a variable whose possible values are numerical outcomes of a random experiment. The Mean (Expected Value) is: μ = Σxp; The Variance is: Var(X) = Σx 2 p − μ 2; The Standard Deviation is: σ = √Var(X)
Expected value uses probability to tell us what outcomes to expect in the long run.
Expected value is a measure of central tendency; a value for which the results will tend to. When a probability distribution is normal, a plurality of the outcomes will be close to the expected value. Any given random variable contains a wealth of information.
Expected value. In probability and statistics, the expected value is the theoretical mean (this assumes that the experiment is run a relatively large number of times) of a random variable, X. For example, the experiment of rolling a fair six-sided die has six possible outcomes, all of which have an equal probability of occurring: {1, 2, 3, 4, 5, 6}
A Random Variable is a set of possible values from a random experiment. The set of possible values is called the Sample Space. A Random Variable is given a capital letter, such as X or Z. Random Variables can be discrete or continuous.
The expected value in statistics is the long-run average outcome of a random variable based on its possible outcomes and their respective probabilities. Essentially, if an experiment (like a game of chance) were repeated, the expected value tells us the average result we’d see in the long run.
Expected value can be used to calculate winning strategies in games of chance, such as board games. Example. As an example, flipping a fair coin has two possible outcomes, heads (denoted here by ) or tails ( ).
