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010   $a3-030-83190-6
024 7 $a10.1007/978-3-030-83190-5
035   $a(MiAaPQ)EBC6841085
035   $a(Au-PeEL)EBL6841085
035   $a(CKB)20462368600041
035   $a(OCoLC)1291317713
035   $a(DE-He213)978-3-030-83190-5
035   $a(PPN)272742023
035   $a(EXLCZ)9920462368600041
100   $a20220104d2022      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aStatistics for Chemical and Process Engineers $eA Modern Approach /$fby Yuri A.W. Shardt
205   $a2nd ed. 2022.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022.
215   $a1 online resource (453 pages)
311 08$a3-030-83189-2 
327   $aIntroduction to Statistics and Data Visualisation -- Theoretical Foundation for Statistical Analysis -- Regression -- Design of Experiments -- Modelling Stochastic Processes with Time Series Analysis -- Modelling Dynamic Processes Using System Identification Methods -- Using MATLAB® for Statistical Analysis -- Using Excel® to do Statistical Analysis.
330   $aA coherent, concise, and comprehensive course in the statistics needed for a modern career in chemical engineering covers all of the concepts required for the American Fundamentals of Engineering Examination. Statistics for Chemical and Process Engineers (second edition) shows the reader how to develop and test models, design experiments and analyze data in ways easily applicable through readily available software tools like MS Excel® and MATLAB® and is updated for the most recent versions of both. Generalized methods that can be applied irrespective of the tool at hand are a key feature of the text, and it now contains an introduction to the use of state-space methods. The reader is given a detailed framework for statistical procedures covering: data visualization; probability; linear and nonlinear regression; experimental design (including factorial and fractional factorial designs); and dynamic process identification. Main concepts are illustrated with chemical- and process-engineering-relevant examples that can also serve as the bases for checking any subsequent real implementations. Questions are provided (with solutions available for instructors) to confirm the correct use of numerical techniques, and templates for use in MS Excel and MATLAB are also available for download. With its integrative approach to system identification, regression, and statistical theory, this book provides an excellent means of revision and self-study for chemical and process engineers working in experimental analysis and design in petrochemicals, ceramics, oil and gas, automotive and similar industries, and invaluable instruction to advanced undergraduate and graduate students looking to begin a career in the process industries.
606   $aChemical engineering
606   $aStatistics
606   $aIndustrial engineering
606   $aProduction engineering
606   $aChemical Engineering
606   $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
606   $aIndustrial and Production Engineering
615  0$aChemical engineering.
615  0$aStatistics.
615  0$aIndustrial engineering.
615  0$aProduction engineering.
615 14$aChemical Engineering.
615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
615 24$aIndustrial and Production Engineering.
676   $a660
676   $a660.015195
700   $aShardt$b Yuri A. W.$01077122
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910522914403321
996   $aStatistics for Chemical and Process Engineers$92588507
997   $aUNINA