## A Course in Probability and StatisticsThis author's modern approach is intended primarily for honors undergraduates or undergraduates with a good math background taking a mathematical statistics or statistical inference course. The author takes a finite-dimensional functional modeling viewpoint (in contrast to the conventional parametric approach) to strengthen the connection between statistical theory and statistical methodology. |

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### Contents

Expectation | 81 |

Special Continuous Models | 134 |

chapter H Special Discrete Models | 162 |

chapter J Dependence | 209 |

Conditioning | 274 |

chapter Normal Models | 338 |

Introduction to Linear Regression | 396 |

chapter u Linear Analysis | 427 |

Orthogonal Arrays | 579 |

chapter L Binomial and Poisson Models | 635 |

Logistic Regression and Poisson Regression | 673 |

Properties of Vectors and Matrices | 751 |

Summary of Probability | 760 |

Summary of Statistics | 774 |

appendix U Hints and Answers | 798 |

Tables | 828 |

chapter IU Linear Regression | 494 |

Copyright | |