## Bayesian Statistical Inference, Issue 43Empirical researchers, for whom Iversen's volume provides an introduction, have generally lacked a grounding in the methodology of Bayesian inference. As a result, applications are few. After outlining the limitations of classical statistical inference, the author proceeds through a simple example to explain Bayes' theorem and how it may overcome these limitations. Typical Bayesian applications are shown, together with the strengths and weaknesses of the Bayesian approach. This monograph thus serves as a companion volume for Henkel's Tests of Significance (QASS vol 4). |

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### Contents

Series Editors Introduction | 5 |

Bayes Theorem | 12 |

Bayesian Methods for a Proportion | 18 |

Bayesian Methods for Other Parameters | 34 |

Prior Distributions | 59 |

Bajesftan Difficulties | 70 |

78 | |

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