<DIV><DIV>Excellent text emphasizes inferential and decision-making statistics. Discusses calculus of probability, sampling procedures, bivariate problems, much more. Problems. Answers.</DIV></DIV>
Introduction to Statistical Inference
β Scribed by Jack Carl Kiefer (auth.), Gary Lorden (eds.)
- Publisher
- Springer-Verlag New York
- Year
- 1987
- Tongue
- English
- Leaves
- 341
- Series
- Springer Texts in Statistics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book is based upon lecture notes developed by Jack Kiefer for a course in statistical inference he taught at Cornell University. The notes were distributed to the class in lieu of a textbook, and the problems were used for homework assignments. Relying only on modest prerequisites of probability theory and calΒ culus, Kiefer's approach to a first course in statistics is to present the central ideas of the modem mathematical theory with a minimum of fuss and formality. He is able to do this by using a rich mixture of examples, pictures, and mathΒ ematical derivations to complement a clear and logical discussion of the important ideas in plain English. The straightforwardness of Kiefer's presentation is remarkable in view of the sophistication and depth of his examination of the major theme: How should an intelligent person formulate a statistical problem and choose a statistical procedure to apply to it? Kiefer's view, in the same spirit as Neyman and Wald, is that one should try to assess the consequences of a statistical choice in some quanΒ titative (frequentist) formulation and ought to choose a course of action that is verifiably optimal (or nearly so) without regard to the perceived "attractiveness" of certain dogmas and methods.
β¦ Table of Contents
Front Matter....Pages i-viii
Introduction to Statistical Inference....Pages 1-3
Specification of a Statistical Problem....Pages 4-22
Classifications of Statistical Problems....Pages 23-30
Some Criteria For Choosing a Procedure....Pages 31-80
Linear Unbiased Estimation....Pages 81-136
Sufficiency....Pages 137-157
Point Estimation....Pages 158-245
Hypothesis Testing....Pages 246-286
Confidence Intervals....Pages 287-311
Back Matter....Pages 312-334
β¦ Subjects
Statistics, general
π SIMILAR VOLUMES
This excellent text emphasizes the inferential and decision-making aspects of statistics. The first chapter is mainly concerned with the elements of the calculus of probability. The second chapter contains the essential statistical techniques of summarizing the data in a sample prior to making infer
<p><span>The complexity of large-scale data sets (βBig Dataβ) has stimulated the development of advanced <br>computational methods for analysing them. There are two different kinds of methods to aid this. The <br>model-based method uses probability models and likelihood and Bayesian theory, while th