# Stats 5ls

rename
eshapeesha's
version from
2016-11-20 22:16

## Section

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

discrete | probability model made up of a list of individual outcomes |

density curve | curve that is always on or above the horizontal axis, has an area of 1 underneath |

discrete vs continuous random variables | discrete must be a whole number, continuous can be any value, decimals included. |

risk | p of undesirable outcome |

odds | p of undesirable outcome/ 1-p |

disjoint | events a and b are disjoint if they have no outcomes in common |

p (b given a) = | P(a and b) / P(a) |

independent | knowing that one event occurs dont not change the probability we would assign to the other events |

P(at least one event occurs) | p(a) + p(b) + p(c) +......... |

P(all events occur) | P(a) x P(b) x......... |

p(a or b) | p(a) + p(b) - p(a and b) |

p(a and b) | p(a) x p(b given a) |

bayes theorem | P(a given b) = p(b given a)p(a)/ p(b given a1)p(a1) + p(b given a2)p(a2)+ ........ |

binomial conditions | fixed n observations, all observations independent, each observation falls is either a success or failure, probability of success is the same for each observation |

binomial mean | np |

binomial probabilty | p(x=k) = p^k (1-p)^n-k |

binomial standard deviation | radical (np(1-p)) |

n choose r = | n!/ r!(n-r)! |

when to estimate with normal distribution | np greater than or = 10, n(1-p) greater than or = 10 |

normal curve rule | (1 sd) contains 68-2 sd contain 95-3 sd contain 99.7 |

z score | x- mean/ standard dev. tells the number of standard deviations away from the mean something is |

cumulative proportion | area of normal curve at and below a given point |

z proportion | tells you amount less than or equal to |

permutatons | nPk= n!/(n-k)! |

combinations | nCk= n!/[(k!)(n-k)!] |

parameter | number that describes a population, (ex- mu) |

statistic | number that can be computed from the sample data without making use of any unknown parameters. (ex- x bar) |

standard deviation of a sample mean | sd/radical n |

standard deviation of a sample proportion | radical [p(1-p)/n] |

when n, np, and n(1-p) are large, and the population is at least 20 x larger than the sample, sd= | radical [np(1-p)/n] |

central limit theorem | for any distribution, as n increases the distribution becomes more normal if it has a stable standard deviation |

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