Question | Answer |

Probability Distribution | A listing of all the outcomes of an experiment and the probability associated with each outcome. |

Characteristics of a Probability Distribution | The probability of a particular outcome is between 0 and 1 inclusive. The outcomes are mutually exclusive events. The list is exhaustive, so the sum of the probabilities of the various events is equal to 1. |

Random Variable | A quantity resulting from an experiment that, by chance, can assume different values. |

Discrete Random Variable | A random variable that can assume only certain clearly separated values. |

Expected Value | The mean of a probability distribution. |

Binomial Probability Distribution | A widely occurring discrete probability distribution. |

What are the binomial characteristics? | An outcome of an experiment is classified into of 2 mutually exclusive categories. The random var counts the number of successes in a fixed number of trials. The probability of success and failure stay the same for each trial. The trials are independent. |

The Greek letter pi is? | The probability of success on each trial. |

n = | The number of trials. |

x = | The random variable defined as the number of successes. |

Poisson Probability Distribution | Describes the number of times some event occurs during a specified interval. The interval may be time, distance, area, or volume. |

What are the characteristics of a Poisson Probability Distribution? | The random variable is the number of times some event occurs during a defined interval. The probability of the event is proportional to the size of the interval. The intervals do not overlap and are independent. |

mu is? | The mean number of occurrences (successes) in a particular interval. |

e is? | The constant 2.71828 (base of the Napierian logarithmic system). |

P(x) is? | The probability for a specified value of x. |

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dengler