eBook: Modern Industrial Statistics (DRM EPUB)
 
電子書格式: DRM EPUB
作者: Ron S. Kenett, Shelemyahu Zacks 
分類: Mathematics  
書城編號: 20727983


售價: $1286.00

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製造商: Wiley
出版日期: 2021/05/18
ISBN: 9781119714965
 
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商品簡介
Modern Industrial Statistics The new edition of the prime reference on the tools of statistics used in industry and services, integrating theoretical, practical, and computer-based approachesModern Industrial Statistics is a leading reference and guide to the statistics tools widely used in industry and services. Designed to help professionals and students easily access relevant theoretical and practical information in a single volume, this standard resource employs a computer-intensive approach to industrial statistics and provides numerous examples and procedures in the popular R language and for MINITAB and JMP statistical analysis software. Divided into two parts, the text covers the principles of statistical thinking and analysis, bootstrapping, predictive analytics, Bayesian inference, time series analysis, acceptance sampling, statistical process control, design and analysis of experiments, simulation and computer experiments, and reliability and survival analysis. Part A, on computer age statistical analysis, can be used in general courses on analytics and statistics. Part B is focused on industrial statistics applications.The fully revised third edition covers the latest techniques in R, MINITAB and JMP, and features brand-new coverage of time series analysis, predictive analytics and Bayesian inference. New and expanded simulation activities, examples, and case studies drawn from the electronics, metal work, pharmaceutical, and financial industries are complemented by additional computer and modeling methods. Helping readers develop skills for modeling data and designing experiments, this comprehensive volume:Explains the use of computer-based methods such as bootstrapping and data visualizationCovers nonstandard techniques and applications of industrial statistical process control (SPC) chartsContains numerous problems, exercises, and data sets representing real-life case studies of statistical work in various business and industry settingsIncludes access to a companion website that contains an introduction to R, sample R code, csv files of all data sets, JMP add-ins, and downloadable appendicesProvides an author-created R package, mistat, that includes all data sets and statistical analysis applications used in the bookPart of the acclaimed Statistics in Practice series, Modern Industrial Statistics with Applications in R, MINITAB, and JMP, Third Edition, is the perfect textbook for advanced undergraduate and postgraduate courses in the areas of industrial statistics, quality and reliability engineering, and an important reference for industrial statisticians, researchers, and practitioners in related fields. The mistat R-package is available from the R CRAN repository.
Ron S. Kenett 作者作品表

Modern Statistics: A Computer-Based Approach with Python (2022) (Paperback)

Industrial Statistics: A Computer-Based Approach with Python (2023) (Hardcover)

Process Improvement and CMMI® for Systems and Software

Shelemyahu Zacks 作者作品表

eBook: Career of a Research Statistician: From Consulting to Theoretical Development (DRM EPUB)

eBook: Career of a Research Statistician: From Consulting to Theoretical Development (DRM PDF)

eBook: Sample Path Analysis and Distributions of Boundary Crossing Times (DRM PDF)

eBook: Sample Path Analysis and Distributions of Boundary Crossing Times (DRM EPUB)

eBook: Examples and Problems in Mathematical Statistics (DRM EPUB)

eBook: Examples and Problems in Mathematical Statistics (DRM PDF)

eBook: Stochastic Visibility in Random Fields (DRM PDF)

eBook: Introduction to Reliability Analysis: Probability Models and Statistical Methods (DRM PDF)

eBook: Stage-Wise Adaptive Designs (DRM PDF)

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