It is a variable which usually the values 0 and 1 depending on the presence and absence of a particular factor in a set of trails. Similarly, the gender of a person could be coded as 0 (= Male) and 1 (= Female) - or the other way around. The actual coding does not matter but it allows for comparisons between the two sub-sets of the population.
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A dummy variable is one that takes the value 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome.
To interpret the coefficient of a dummy variable is to follow all of the steps of the equation that is being used as if the dummy variable was a real one.
There are various forms. In linear programming, a dummy variable may be used to convert an inequality into an equation. For example x < 10 can be written as x + u = 10 where u > 0. In this case, it is also called a slack variable. Dummy variables are used in regression to indicate the presence or absence of a factor, or for binary variables. For example, male/female could be coded numerically as 0/1 where, because the question is binary, the exact coding does not matter.
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To find the Z score from the random variable you need the mean and variance of the rv.To find the Z score from the random variable you need the mean and variance of the rv.To find the Z score from the random variable you need the mean and variance of the rv.To find the Z score from the random variable you need the mean and variance of the rv.
For a continuous variable it is 0.5 but for a discrete variable the answer depends on the probability of the variable taking the mean value. It is half of the rest of the probability. If the discrete variable X has mean m and Prob(X = m) is p then Prob(X > m) = (1 - p)/2.