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Business Statistics
Chapter 5
| Question | Answer |
|---|---|
| Random Variable | Numerical description of the outcome of an experiment |
| Discrete Random Variable | A random variable that may assume either a finite number of values or an infinite sequence of values |
| Continuous Random Variable | A random variable that may assume any numerical value in an interval or collection |
| Probability Distribution | Describes how probabilities are distributed over the values of random variable |
| Probability Function | denoted by f(x) provides the probability for each value of the random variable |
| Empirical Discrete Distribution | The use of the relative frequency method to develop discrete probabilaty distribution is what leads us to EDD. |
| Required Conditions for a Discrete Probability Function | f(x) > or equal to 0 Ef(x) = 1 |
| Discrete Uniform Probability Distribution Function | f(x) = 1/n where n= the number of values the random variable may assume |
| Expected Value | is a weighted average of the values of the random variable where the weights are the probabilities |
| Variance of a Discrete Random Variable | Var(x) - o2 = E(x-u)2f(x) The variance is a weighted average of the squared deviations of a random variable from its mean. The weights are the probabilites |
| Standard Deviation, o | is defined as the positive square root of the variance |
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