Author: United States. Bureau of the CensusPublisher:
ISBN:
Category : Manufactures
Languages : en
Pages : 116
Book Description
Guide to Industrial Statistics
Author: United States. Bureau of the CensusPublisher:
ISBN:
Category : Manufactures
Languages : en
Pages : 116
Book Description
Guide to Industrial Statistics
Author: United States. Bureau of the CensusPublisher:
ISBN:
Category : Manufactures
Languages : en
Pages : 0
Book Description
Guide to Industrial Statistics
Author: United States. Bureau of the CensusPublisher:
ISBN:
Category : Manufacturing industries
Languages : en
Pages : 68
Book Description
Guide to Industrial Statistics
Author: Etats-Unis. Census bureauPublisher:
ISBN:
Category :
Languages : en
Pages : 105
Book Description
Guide to Industrial Statistics
Author: Guide to Industrial Statistics
Author: United States. Bureau of the CensusPublisher:
ISBN:
Category : Manufactures
Languages : en
Pages : 116
Book Description
Industrial Statistics
Author: United States. Bureau of the CensusPublisher:
ISBN:
Category : Manufactures
Languages : en
Pages : 68
Book Description
Modern Industrial Statistics
Author: Ron S. KenettPublisher: John Wiley & Sons
ISBN: 1119714923
Category : Mathematics
Languages : en
Pages : 880
Book Description
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 approaches Modern 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 visualization Covers nonstandard techniques and applications of industrial statistical process control (SPC) charts Contains numerous problems, exercises, and data sets representing real-life case studies of statistical work in various business and industry settings Includes 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 appendices Provides an author-created R package, mistat, that includes all data sets and statistical analysis applications used in the book Part 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.
Guide to Industrial Analytics
Author: Richard HillPublisher: Springer Nature
ISBN: 3030791041
Category : Computers
Languages : en
Pages : 285
Book Description
This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.
Author: