000			03487nam a22003617a 4500
003			ZW-GwMSU
005			20240304132207.0
008			240226b |||||||| |||| 00| 0 eng d
020			_a9781119714903
040			_arda _bEnglish _erda _cMSULIB
050	0	0	_aTS156 KEN
100	1		_aKenett, Ron _eauthor.
245	1	0	_aModern industrial statistics : _bwith applications in R, MINITAB and JMP / _ccreated by Ron S. Kenett, Shelemyahu Zacks with contributions from Daniele Amberti
250			_aThird edition.
264		1	_bJohn Wiley and Sons, _c2021.
264		4	_c©2021.
300			_axxv, 849 pages : _billustrations ; _c24 cm
336			_2rdacontent _atext
337			_aunmediated _2rdamedia _bn
338			_2rdacarrier _avolume _bnc
490	0		_aStatistics in practice
504			_aIncludes bibliographical references and index.
505			_aPreface to the third edition Preface to the second edition (abbreviated) Preface to the first edition (abbreviated) List of abbreviations Part A: Modern Statistics: A Computer Based Approach 1 Statistics and Analytics in Modern Industry 2 Analyzing Variability: Descriptive Statistics 3 Probability Models and Distribution Functions 4 Statistical Inference and Bootstrapping 5 Variability in Several Dimensions and Regression Models 6 Sampling for Estimation of Finite Population Quantities 7. Time Series Analysis and Prediction 8 Modern analytic methods Part B: Modern Industrial Statistics: Design and Control of Quality and Reliability 9 The Role of Industrial Analytics in Modern Industry 10 Basic Tools and Principles of Process Control 11 Advanced Methods of Statistical Process Control 12 Multivariate Statistical Process Control 13 Classical Design and Analysis of Experiments 14 Quality by Design 15 Computer Experiments 16 Reliability Analysis 17 Bayesian Reliability Estimation and Prediction 18 Sampling Plans for Batch and Sequential Inspection List of R packages References Author index Subject index Solution manual Appendices (available on book?s website) Appendix I Intro to R Appendix II Intro to MINITAB and Matrix Algebra Appendix III R scripts Appendix IV mistat Appendix V csv Files Appendix VI MINITAB macros Appendix VII JMP scripts
520			_a"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"--
650		0	_aQuality control _xStatistical methods.
650		0	_aReliability (Engineering) _xStatistical methods.
650		0	_aR (Computer program language)
700	1		_aZacks, Shelemyahu, _d1932- _eauthor.
700	1		_aAmberti, Daniele, _eauthor.
776	0	8	_iOnline version: _aKenett, Ron S., _tModern industrial statistics _bThird edition. _dHoboken : Wiley, 2021. _z9781119714927 _w(DLC) 2020051134
830		0	_aStatistics in practice
942			_2lcc _cB
999			_c163772 _d163772