Books like Statistical theory and methodology in science and engineering by K. A. Brownlee


First publish date: 1965
Subjects: Statistics, Politics and government, Science, Foreign relations, Textbooks
Authors: K. A. Brownlee
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Statistical theory and methodology in science and engineering by K. A. Brownlee

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Books similar to Statistical theory and methodology in science and engineering (16 similar books)

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xiv, 766 p. : 25 cm

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πŸ“˜ Schaum's outline of theory and problems of statistics in SI units

Study faster, learn better-and get top grades with Schaum's OutlinesMillions of students trust Schaum's Outlines to help them succeed in the classroom and on exams. Schaum's is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, solved problems, and practice exercises to test your skills.Use Schaum's Outlines to:Brush up before testsFind answers fastStudy quickly and more effectivelyGet the big picture without spending hours poring over lengthy textbooksFully compatible with your classroom text, Schaum's highlights all the important facts you need to know. Use Schaum's to shorten your study time-and get your best test scores!This Schaum's Outline gives you:A concise guide to the standard college course in statistics486 fully worked problems of varying difficulty660 additional practice problems

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πŸ“˜ Bayesian data analysis

"Bayesian Data Analysis is a comprehensive treatment of the statistical analysis of data from a Bayesian perspective. Modern computational tools are emphasized, and inferences are typically obtained using computer simulations.". "The principles of Bayesian analysis are described with an emphasis on practical rather than theoretical issues, and illustrated using actual data. A variety of models are considered, including linear regression, hierarchical (random effects) models, robust models, generalized linear models and mixture models.". "Two important and unique features of this text are thorough discussions of the methods for checking Bayesian models and the role of the design of data collection in influencing Bayesian statistical analysis." "Issues of data collection, model formulation, computation, model checking and sensitivity analysis are all considered. The student or practising statistician will find that there is guidance on all aspects of Bayesian data analysis."--BOOK JACKET.

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πŸ“˜ Applied linear statistical models
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πŸ“˜ Introduction to statistics


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πŸ“˜ Introductory statistics


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πŸ“˜ Statistical inference


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πŸ“˜ Understandable statistics

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πŸ“˜ Elementary Statistics


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πŸ“˜ Introduction to the Theory of Statistics


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πŸ“˜ Probability and statistics for engineers


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πŸ“˜ Probability and statistics

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a new chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), expanded coverage of residual analysis in linear models, and more examples using real data.

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All of Statistics: A Concise Course in Statistical Inference by Larry Wasserman
Applied Statistical Inference by George Casella
Mathematical Statistics and Data Analysis by John A. Rice
Statistical Methods for Data Analysis by John Neter, William Wasserman, Michael H. Kutner

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