Expected Value for a Discrete Random Variable. E(X)=\sum x_i p_i. x_i= value of the i th outcome p_i = probability of the i th outcome. According to this formula. The expected value plays important roles in a variety of contexts. In regression analysis, one desires a formula in terms of observed data that will give a "good" Definition · General definition · Properties · Uses and applications. Anticipated value for a given investment. In statistics and probability analysis, expected value is calculated by multiplying each of the possible outcomes by the. The assigned value of each outcome will be positive if you expect to earn money and negative if you expect to lose. This type of expected value is called an expected value for a binomial random variable. Assign a value to each possible outcome. Use the expected value formula to obtain:. As with any EV problem, you must begin by defining all possible outcomes. It follows directly from the discrete case definition that if X is a constant random variable , i. Become a day trader.
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