# C1

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2017-06-27 03:17

## Section

Question | Answer |
---|---|

Continuous Random Variable | A random variable that may assume any numerical value in an interval or collection of intervals |

Sampled population | is the population from the sample is drawn |

Statistical Inference | the process of obtaining data from a sample to make estimates or test hypotheses about the characteristics. |

Parameter | a numerical characteristic of a population |

Frame | is a listing of the elements that the sample will be selected |

Sample Statistic | the corresponding characteristic of the sample in order to estimate the value of a population parameter. |

Point Estimator | The sample statistic x, s or p that provides the point estimate of the population |

Target Population | the population for which statistical inference such as point estimates are made. It is important the target population to correspond closely to the sample population. |

Unbiased | a property of a point estimator that is present when the expected value of the point estimator is equal to the population parameter it estimates. |

Standard error | the standard deviation of a point estimator |

Sampling error | The difference between an unbiased point estimate and the corresponding population parameter is called |

Sampling Distribution | is a probability distribution consisting of all possible values of a sample statistic. |

Central Limit Theorem | a theorem that enables one to use the normal probability distribution to approximate the sampling distribution of x whenever the sample size is large |

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