Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Описание: Covering everything from basic principles to state-of-the-art concepts and applications, this book arms readers with a comprehensive understanding of modern statistical methods for quality control and improvement. The authors cover basic and advanced methods of statistical process control (SPC), show how statistically designed experiments can be used for process design, development and improvement, and explore acceptance sampling. Throughout the pages, guidelines are provided for selecting the correct statistical technique to use in a variety of situations.
Автор: Alfred Bartolucci, Karan P. Singh, Sejong Bae Название: Introduction to Statistical Analysis of Laboratory Data ISBN: 1118736869 ISBN-13(EAN): 9781118736869 Издательство: Wiley Рейтинг: Цена: 16466.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis
Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process
Introduces terminology used in many applications such as the interpretation of assay design and validation as well as "fit for purpose" procedures including real world examples
Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities
Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation
Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions
Автор: Efron Название: An Introduction to the Bootstrap ISBN: 0412042312 ISBN-13(EAN): 9780412042317 Издательство: Taylor&Francis Рейтинг: Цена: 22968.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.
Автор: Nachtsheim;Neter;Kutner Название: Applied Linear Statistical Models with Student CD ISBN: 0071122214 ISBN-13(EAN): 9780071122214 Издательство: McGraw-Hill Рейтинг: Цена: 9265.00 р. Наличие на складе: Поставка под заказ.
Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
Автор: Victor A. Skormin Название: Introduction to Process Control ISBN: 331942257X ISBN-13(EAN): 9783319422572 Издательство: Springer Рейтинг: Цена: 10760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers: Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications. Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models. Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control. Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning. Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured. Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.
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