## Elementary Decision TheoryBeginners will find this well-respected introduction to statistics and statistical theory a motivating introduction to important mathematical notions such as set, function, and convexity. Other topics include data processing, probability, and random variables, models, testing hypotheses, and much more. Clearly written, brief, well-indexed, and abundantly equipped with exercise material. 1959 edition. |

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NOT TOO SHABBY

### Contents

CHAPTER PAGE | 1 |

Principles Used in Decision Making | 9 |

DATA PROCESSING | 17 |

Known Variance | 18 |

INTRODUCTION TO PROBABILITY AND RANDOM VARIABLES | 41 |

TABLES OF PROBABILITY DISTRIBUTIONS | 92 |

5 | 118 |

Summary | 295 |

Alternative the Bayes Strategies are Likelihood | 332 |

Es Some Sequential LikelihoodRatio Tests | 344 |

PARTIAL LIST OF ANSWERS TO EXERCISES | 353 |

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### Common terms and phrases

accept action action probabilities admissible apply approximately assume assumptions average average loss Bayes strategy boundary called Chapter close coin compute consider consists convenient convex set corresponding cumulative curve decide decision density depend discrete discussion equal Equation error estimate evaluate example Exercise expected loss experiment face fact falls Figure frequency function give given graph hand heads Hence ideal illustrate important increases indicate interested interval involves known mean measure method minimax nature normally distributed Note observations obtained outcome points population positive possible preferred present priori probabilities probability distribution problem prospect random variable reasonable regret relative replacement represented respectively risk sample sample mean simple standard deviation statistical statistician Suppose Table tend theory tion tires toss utility variance wear weighted yield