| A | B |
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| Random variable | A random variable assumes any of several different values as a result of some random event. Random variables are denoted by a capital letter such as X |
| Discrete random variable | A random variable that can take one of a finite number of distnct outcomes is called a discrete random variable. |
| Continuous random variable | A ranadom variable that can take any numceric value within a range of values is called a continuous random variable. The range may be infinite or bounded at either or both ends |
| Probability model | The probability model is a function that associates a probability P with each value of a discrete random variable X, denoted P(X = x), or with any intervalof values of a continuous random variable. |
| Expected value | The theoretical long-run average value - center of model - denoted u or E(X) - sum of variable values and probabilities |
| Variance | The variance of a random variable is the expected value of the squared deviation form the mean. |
| Standard deviation | The standard deviation of a random variable descrebes the spread in the model, and is the square root of the variance |
| The square root of the variance | standard deviation |
