Incorporating the latest information on developments in the field of statistical inference, this book looks at various approaches to point estimation, hypotheses testing, interval estimation and model building. Intended to be a handbook, it concentrates on ideas (rather than comprehensive theorem-proving), and contains many exercises. Although it is written at a fairly advanced level, the book employs only the necessary mathematics for a full understanding of the text. Topics covered include a discussion on the properties of estimators and methods of estimation, hypotheses testing and interval estimation. Both the classical and decision theory/Bayesian approaches are covered. Other topics which are described more briefly include, amongst others, robust and non-parametric procedures, computationally intensive methods and generalized linear models.
"synopsis" may belong to another edition of this title.
Byron Jones is Professor of Medical Statistics at De Montfort University.
Incorporating the latest information on development in the field of statistical inference, this book looks at various approaches to point estimation, hypotheses testing, interval estimation and model building. It concentrates on ideas (rather than comprehensive theorem-proving), contains many exercises, and although it is written at a fairly advanced level, the book employs only the necessary mathematics for a full understanding of the text. For researchers in mathematics, medicine, biology and agriculture needing knowledge of the theory of making inferences from observed data.
"About this title" may belong to another edition of this title.
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