Modern industrial statistics : with applications in R, MINITAB and JMP / Ron S. Kenett, Chairman and CEO, the KPA Group, Raanana, Israel Research Professor, University of Turin, Turin, Italy, and Senior Research Fellow, Samuel Neaman Institute for National Policy Research, Technion, Israel, Shelemyahu Zacks, Distinguished Professor, Binghamton University, Binghamton, USA ; with contributions from Daniele Amberti, Turin, Italy.
- 作者： Kenett, Ron, author.
- 其他作者：
- 其他題名：
- With applications in R, MINITAB and JMP
- Statistics in practice.
- 出版： Hoboken, NJ : Wiley 2021.
- 叢書名： Statistics in practice
- 主題： Quality control--Statistical methods. , R (Computer program language) , Reliability (Engineering)--Statistical methods. , JMP (Computer file) , Minitab.
- 版本：3rd ed.
- ISBN： 9781119714903 (hbk.) :: NT 、 9781119714927 (adobe pdf) 、 1119714923 (adobe pdf)
- 一般註：Previous edition: 2014.
- 書目註：Includes bibliographical references and index.
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讀者標籤：
- 系統號： 005170849 | 機讀編目格式
館藏資訊
摘要註
"Industrial Statistics is concerned with maintaining and improving the quality of goods and services. It involves a broad range of statistical tools but maintaining and improving quality is its main concern. Variability is inherent in all processes, whether they be manufacturing processes or service processes. This variability must be controlled to create high quality goods and services and must be reduced to improve quality. Industrial Statistics focuses on the use of statistical thinking, i.e., the appreciation of the inherent variability of all processes in order that all possible outcomes can be assessed. It also focuses on developing skills for modeling data and designing experiments that can lead to improvements in performance and reductions in variablity"--
內容註
Modern Statistics: A Computer-Based Approach. Statistics and Analytics in Modern Industry -- M.odern Statistics: A Computer-Based Approach. Analyzing Variability: Descriptive Statistics -- Probability Models and Distribution Functions -- Statistical Inference and Bootstrapping -- Variability in Several Dimensions and Regression Models -- Sampling for Estimation of Finite Population Quantities -- Time Series Analysis and Prediction -- Modern Analytic Methods -- Modern Industrial Statistics: Design and Control of Quality and Reliability. The Role of Statistical Methods in Modern Industry and Services -- Basic Tools and Principles of Process Control -- Advanced Methods of Statistical Process Control -- Multivariate Statistical Process Control -- Classical Design and Analysis of Experiments -- Quality by Design -- Computer Experiments -- Reliability Analysis -- Bayesian Reliability Estimation and Prediction -- Sampling Plans for Batch and Sequential Inspection -- List of R Packages -- Solution Manual.