000 04192nam a22003615i 4500
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008 150903s2006 xxk| o |||| 0|eng d
020 _a9781846282881
_99781846282881
024 7 _a10.1007/9781846282881
_2doi
035 _avtls000343787
039 9 _a201509030355
_bVLOAD
_c201405050258
_dVLOAD
_y201402061204
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTA169.7
100 1 _aPham, Hoang.
_eeditor.
_9305519
245 1 0 _aSpringer Handbook of Engineering Statistics /
_cedited by Hoang Pham.
264 1 _aLondon :
_bSpringer London,
_c2006.
300 _aeReference.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
505 0 _aPart A Fundamental Statistics and its Applications -- Part B Process Monitoring and Improvement -- Part C Reliability Models and Survival Analysis -- Part D Regression Methods and Data Mining -- Part E Statistical Methods and Modeling -- Part F Applications in Engineering Statistics -- About the Authors -- Subject Index.
520 _aEngineers and practitioners contribute to society through their ability to apply basic scientific principles to real problems in an effective and efficient manner. They must collect data to test their products every day as part of the design and testing process and also after the product or process has been rolled out to monitor its effectiveness. Model building and validation, data collection, data analysis and data interpretation form the core of sound engineering practice. After the data has been gathered the engineers, statisticians, designers, and practitioners must be able to sift them and interpret them correctly so that meaning can be exposed from a mass of undifferentiated numbers or facts. To do this he must be familiar with the fundamental concepts of correlation, uncertainty, variability and risk in the face of uncertainty. In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. Many organizations have shown that the first step to continuous improvement is to integrate the widespread use of statistics and basic data analysis into the manufacturing development process as well as into the day-to-day business decisions taken in regard to engineering and technological information processes. The Springer Handbook of Engineering Statistics gathers together the full range of statistical techniques required by readers from all fields to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. Key Topics Fundamental Statistics Process Monitoring and Improvement Reliability Modeling and Survival Analysis Regression Methods Data Mining Statistical Methods and Modeling Wide Range of Applications including Six Sigma Features Contributions from leading experts in statistics and their application to engineering from industrial control to academic medicine and financial risk management Wide-ranging selection of statistical techniques to enable the readers to choose the method most appropriate Extensive and easy-to-use subject index making information quickly available to the reader. The Springer Handbook of Engineering Statistics will be essential reading for all engineers, statisticians, researchers, teachers, students, and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781852338060
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-84628-288-1
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c291762
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