## Probability & StatisticsA developed, complete treatment of undergraduate probability and statistics by a very well known author. The approach develops a unified theory presented with clarity and economy. Included many examples and applications. Appropriate for an introductory undergraduate course in probability and statistics for students in engineering, math, the physical sciences, and computer science.(vs. Walpole/Myers, Miller/Freund, Devore, Scheaffer/McClave, Milton/Arnold) |

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### Contents

Fundamental Concepts | 19 |

Repeated Trials | 59 |

The Random Variable | 84 |

Copyright | |

10 other sections not shown

### Common terms and phrases

approximation assume assumption average axioms binomial distribution coin conclude conditional conditional probability confidence interval consists constant corresponding critical region curve denote determine discrete type distribution F(x elementary events elements entropy equals equation Example expected values experiment exponential Figure Find the 95 Find the probability follows Fq(q function F(x fx(x Fy(y fz(z given hence hypothesis H0 independent rvs integral interval estimate joint density likelihood function linear maximum ML estimates normal rv Note null hypothesis observe obtain occurs outcomes P(si P(sl partition percentile points Poisson Poisson distribution prediction problem Proof random ratio reject H0 repeated trials rn sequence rv x sample mean Section specific staircase function sufficient statistic Suppose takes the values test statistic test the hypothesis theorem tion toss Type II error typical sequences variable variance wish to test yields