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Ten projects in applied statistics

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Ten projects in applied statistics/ by Peter McCullagh.
作者:	McCullagh, P.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xix, 412 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Data Analysis and Big Data. -
電子資源:	https://doi.org/10.1007/978-3-031-14275-8
ISBN:	9783031142758

Ten projects in applied statistics
McCullagh, P.

Ten projects in applied statistics[electronic resource] /by Peter McCullagh. - Cham :Springer International Publishing :2022. - xix, 412 p. :ill., digital ;24 cm. - Springer series in statistics,2197-568X. - Springer series in statistics..

1. Rat Surgery -- 2. Chain Saws -- 3. Fruit Flies -- 4. Growth Curves -- 5. Louse Evolution -- 6. Time Series I -- 7. Time Series II -- 8. Out of Africa -- 9. Environmental Projects -- 10. Fulmar Fitness -- 11. Basic Concepts -- 12. Principles -- 13. Initial Values -- 14. Probability Distributions -- 15. Gaussian Distributions -- 16. Space-Time Processes -- 17. Likelihood -- 18. Residual Likelihood -- 19. Response Transformation -- 20. Presentations and Reports -- 21. Q & A.

The first half of the book is aimed at quantitative research workers in biology, medicine, ecology and genetics. The book as a whole is aimed at graduate students in statistics, biostatistics, and other quantitative disciplines. Ten detailed examples show how the author approaches real-world statistical problems in a principled way that allows for adequate compromise and flexibility. The need to accommodate correlations associated with space, time and other relationships is a recurring theme, so variance-components models feature prominently. Statistical pitfalls are illustrated via examples taken from the recent scientific literature. Chapter 11 sets the scene, not just for the second half of the book, but for the book as a whole. It begins by defining fundamental concepts such as baseline, observational unit, experimental unit, covariates and relationships, randomization, treatment assignment, and the role that these play in model formulation. Compatibility of the model with the randomization scheme is crucial. The effect of treatment is invariably modelled as a group action on probability distributions. Technical matters connected with space-time covariance functions, residual likelihood, likelihood ratios, and transformations are discussed in later chapters.

ISBN: 9783031142758

Standard No.: 10.1007/978-3-031-14275-8doiSubjects--Topical Terms:

1366136
Data Analysis and Big Data.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Ten projects in applied statistics
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