Introduction to Experimental Statistics PDF Download
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Author: Ching Chun Li
Publisher:
ISBN:
Category : Biometry
Languages : en
Pages : 490
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Book Description
Author: Ching Chun Li
Publisher:
ISBN:
Category : Biometry
Languages : en
Pages : 490
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Book Description
Author: David Heath
Publisher: CRC Press
ISBN: 9780203499245
Category : Mathematics
Languages : en
Pages : 390
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Book Description
This illustrated textbook for biologists provides a refreshingly clear and authoritative introduction to the key ideas of sampling, experimental design, and statistical analysis. The author presents statistical concepts through common sense, non-mathematical explanations and diagrams. These are followed by the relevant formulae and illustrated by w
Author: John Mandel
Publisher: Courier Corporation
ISBN: 048613959X
Category : Mathematics
Languages : en
Pages : 432
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Book Description
First half of book presents fundamental mathematical definitions, concepts, and facts while remaining half deals with statistics primarily as an interpretive tool. Well-written text, numerous worked examples with step-by-step presentation. Includes 116 tables.
Author: Mary Gibbons Natrella
Publisher: Courier Corporation
ISBN: 0486154556
Category : Mathematics
Languages : en
Pages : 562
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Book Description
A handbook for those seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Covers the planning of experiments, the analyzing of extreme-value data; and more. 1966 edition. Index. Includes 52 figures and 76 tables.
Author: Hugh D. Young
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 196
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Book Description
Even with a limited mathematics background, readers can understand what statistical methods are & how they may be used to obtain the best possible results from experimental measurements & data.
Author: Richard A. Chechile
Publisher: MIT Press
ISBN: 0262044587
Category : Mathematics
Languages : en
Pages : 473
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Book Description
An introduction to the Bayesian approach to statistical inference that demonstrates its superiority to orthodox frequentist statistical analysis. This book offers an introduction to the Bayesian approach to statistical inference, with a focus on nonparametric and distribution-free methods. It covers not only well-developed methods for doing Bayesian statistics but also novel tools that enable Bayesian statistical analyses for cases that previously did not have a full Bayesian solution. The book's premise is that there are fundamental problems with orthodox frequentist statistical analyses that distort the scientific process. Side-by-side comparisons of Bayesian and frequentist methods illustrate the mismatch between the needs of experimental scientists in making inferences from data and the properties of the standard tools of classical statistics. The book first covers elementary probability theory, the binomial model, the multinomial model, and methods for comparing different experimental conditions or groups. It then turns its focus to distribution-free statistics that are based on having ranked data, examining data from experimental studies and rank-based correlative methods. Each chapter includes exercises that help readers achieve a more complete understanding of the material. The book devotes considerable attention not only to the linkage of statistics to practices in experimental science but also to the theoretical foundations of statistics. Frequentist statistical practices often violate their own theoretical premises. The beauty of Bayesian statistics, readers will learn, is that it is an internally coherent system of scientific inference that can be proved from probability theory.
Author: Michael H. Herzog
Publisher: Springer
ISBN: 3030034992
Category : Science
Languages : en
Pages : 146
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Book Description
This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
Author: Walter Anton Hendricks
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 260
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Book Description
Author: Oliver L. Lacey
Publisher:
ISBN:
Category : Experimental design
Languages : en
Pages : 272
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Book Description
Author: Steve Miller
Publisher: Routledge
ISBN: 1134954638
Category : Psychology
Languages : en
Pages : 158
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Book Description
The distinguishing feature of experimental psychology is not so much the nature of its theories as the methods used to test their validity. The first edition of Experimental Design and Statistics provided a clear and lucid introduction to these methods and the statistical techniques which support them. For this new edition the text has been revised, the coverage of two-sample tests has been extended, and new sections have been added introducing one-sample tests, linear regression and the product-moment correlation coefficient. Problems associated with the applications of experimental design and how to use observations of behaviour in research are key questions for all introductory students of psychology. This new and expanded edition provides them with an invaluable text and source.
