Nonparametric Statistical Techniques in Bioassay PDF Download

Author: Maiying Kong
Publisher:
ISBN:
Category :
Languages : en
Pages : 194

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Author: Z. Govindarajulu
Publisher: Karger Medical and Scientific Publishers
ISBN: 3805571194
Category : Science
Languages : en
Pages : 249

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Book Description
In the face of the ever-increasing importance of statistical methods in medical research and practice, the first edition of this publication has provided a sound and deep understanding of statistical methods in bioassay to many students and researchers. In addition to the profound presentation of statistical methods of the first edition, here the reader will find new material stemming from the recent statistical literature as well as data reflecting modern trends in general applied statistical research. Examples are discussions on design and planning, e.g. choices of dose levels, and additional section in the chapter on Bayes methods, and a new chapter on sequential estimation for the logistic model. The book will be a valuable source of information to students in the experimental area of statistical aspects of biological assay, professional statisticians with an interest in research in this topic, teachers in statistics and biology, and investigators in the biological and medical sciences who use bioassay in their work.

Author: David John Finney
Publisher:
ISBN:
Category : Biological assay
Languages : en
Pages : 700

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Author: Myles Hollander
Publisher: John Wiley & Sons
ISBN: 1118553292
Category : Mathematics
Languages : en
Pages : 872

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Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.

Author: C. I. Bliss
Publisher: Elsevier
ISBN: 1483277011
Category : Medical
Languages : en
Pages : 189

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Book Description
The Statistics of Bioassay: With Special Reference to the Vitamins, Volume II focuses on the processes, reactions, principles, and approaches involved in the biological assay of vitamins. The publication first offers information on the general principles of biological assay, dosage-response curve and its error, and designs for segregating nonrandom variation. Discussions focus on replacement of missing values, randomized groups, calculation of the line, analysis of the variation about the line, comparative biological assays, analytical biological assays, and determination of activity. The text then ponders on measurement of relative potency and correction of quantitative variables. The manuscript takes a look at assays where the variation in response is a function of the dose and slope-ratio assays. Topics include microbiological assays and the slope-ratio technique, analysis of balanced slope-ratio assays, analysis of assays with an all-or-none response, and graded response with unequal variance. The publication then tackles multiple or repeated assays, including quality control in repeated assays and combination of independent assays of a single unknown. The publication is a valuable source of information for researchers interested in the biological assay of vitamins.

Author: Jean Dickinson Gibbons
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 504

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Author: M.M. Desu
Publisher: CRC Press
ISBN: 1482285894
Category : Mathematics
Languages : en
Pages : 384

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Book Description
Balancing the "cookbook" approach of some texts with the more mathematical approach of others, Nonparametric Statistical Methods for Complete and Censored Data introduces commonly used non-parametric methods for complete data and extends those methods to right censored data analysis. Whenever possible, the authors derive their methodology from the

Author: Peter Sprent
Publisher: Springer Science & Business Media
ISBN: 9400912234
Category : Science
Languages : en
Pages : 268

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Book Description
This book is a practical introduction to statistical techniques called nonpara metric methods. Using examples, we explain assumptions and demonstrate procedures; theory is kept to a minimum. We show how basic problems are tackled and try to clear up common misapprehensions so as to help both students of statistics meeting the methods for the first time and workers in other fields faced with data needing simple but informative analysis. An analogy between experimenters and car drivers describes our aim. Statistical analyses may be done by following a set of rules without understanding their logical basis, but this has dangers. It is like driving a car with no inkling ofhow the internal combustion engine, the gears, the ignition system, the brakes actually work. Understanding the rudiments helps one get better performance and makesdrivingsafer;appropriate gearchanges become a way to reduce engine stress, prolong engine life, improve fuel economy, minimize wear on brake linings. Knowing how to change the engine oil or replace worn sparking plugs is notessential for adriver, but it will reduce costs. Learning such basics will not make one a fully fledged mechanic, even less an automotive engineer; but it all contributes to more economical and safer driving, alertingone to the dangers ofbald tyres, aleakingexhaust, worn brake linings.

Author: John Kloke
Publisher: CRC Press
ISBN: 1040025153
Category : Mathematics
Languages : en
Pages : 466

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Book Description
Praise for the first edition: “This book would be especially good for the shelf of anyone who already knows nonparametrics, but wants a reference for how to apply those techniques in R.” -The American Statistician This thoroughly updated and expanded second edition of Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses. Two new chapters covering multivariate analyses and big data have been added. Core classical nonparametrics chapters on one- and two-sample problems have been expanded to include discussions on ties as well as power and sample size determination. Common machine learning topics --- including k-nearest neighbors and trees --- have also been included in this new edition. Key Features: Covers a wide range of models including location, linear regression, ANOVA-type, mixed models for cluster correlated data, nonlinear, and GEE-type. Includes robust methods for linear model analyses, big data, time-to-event analyses, timeseries, and multivariate. Numerous examples illustrate the methods and their computation. R packages are available for computation and datasets. Contains two completely new chapters on big data and multivariate analysis. The book is suitable for advanced undergraduate and graduate students in statistics and data science, and students of other majors with a solid background in statistical methods including regression and ANOVA. It will also be of use to researchers working with nonparametric and rank-based methods in practice.

Author: T.V. Mzolo
Publisher:
ISBN: 9789038640518
Category :
Languages : en
Pages : 162

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