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Statistical inference in science. (English) Zbl 0955.62006
Springer Series in Statistics. New York, NY: Springer. xv, 245 p. (2000).
The main purpose of this book is to present statistical methods appropriate for the analysis of repeatable experiments in science. It emphasizes techniques for dividing the sample information into various parts addressing the diverse problems of inference that arise from such experiments. A valuable feature of the book is the large number of practical examples, many of which use data taken from experiments published in scientific journals. This book would be a suitable textbook for advanced undergraduate, master, and Ph.D. students. It assumes an introductory course in probability, including the calculation of probability functions and densities, and transformations of variables using Jacobians.
Chapter headings: (1) Introduction; (2) Likehood function; (3) Division of sample information I; (4) Division of sample information II: likehood structure; (5) Estimation statements; (6) Tests of significance; (7) Location-scale pivotal model; (8) Gauss linear model; (9) Maximum likehood estimation; (10) Controlled experiments; (11) Problems.

MSC:
62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
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