Practical Data Analysis in Chemistry

2007-08-10
 |  Science
Practical Data Analysis in Chemistry

Author: Marcel Maeder

Publisher: Elsevier

ISBN: 0080548830

Category: Science

Page: 340

View: 932

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The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes. The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications. Finally Chapter 5 comprises a collection of several methods for model-free data analyses. * Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes. * Provides examples of routines that are easily adapted to the processes investigated by the reader * 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered

Chemometrics in Practical Applications

2012-03-23
 |  Science
Chemometrics in Practical Applications

Author: Kurt Varmuza

Publisher: BoD – Books on Demand

ISBN: 9789535104384

Category: Science

Page: 342

View: 365

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In the book "Chemometrics in practical applications", various practical applications of chemometric methods in chemistry, biochemistry and chemical technology are presented, and selected chemometric methods are described in tutorial style. The book contains 14 independent chapters and is devoted to filling the gap between textbooks on multivariate data analysis and research journals on chemometrics and chemoinformatics.

Chemometrics in Excel

2014-05-19
 |  Science
Chemometrics in Excel

Author: Alexey L. Pomerantsev

Publisher: John Wiley & Sons

ISBN: 9781118605356

Category: Science

Page: 338

View: 141

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Providing an easy explanation of the fundamentals, methods, and applications of chemometrics • Acts as a practical guide to multivariate data analysis techniques • Explains the methods used in Chemometrics and teaches the reader to perform all relevant calculations • Presents the basic chemometric methods as worksheet functions in Excel • Includes Chemometrics Add In for download which uses Microsoft Excel® for chemometrics training • Online downloads includes workbooks with examples

Comprehensive Chemometrics

2020-05-26
 |  Science
Comprehensive Chemometrics

Author: Steven Brown

Publisher: Elsevier

ISBN: 9780444641663

Category: Science

Page: 2944

View: 353

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Comprehensive Chemometrics, Second Edition features expanded and updated coverage, along with new content that covers advances in the field since the previous edition published in 2009. Subject of note include updates in the fields of multidimensional and megavariate data analysis, omics data analysis, big chemical and biochemical data analysis, data fusion and sparse methods. The book follows a similar structure to the previous edition, using the same section titles to frame articles. Many chapters from the previous edition are updated, but there are also many new chapters on the latest developments. Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience

Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling

2022-11-01
 |  Science
Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling

Author: Jahan B. Ghasemi

Publisher: Elsevier

ISBN: 9780323907064

Category: Science

Page: 212

View: 303

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Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical analysis, the book then explores multivariate calibration and validation methods. Soft modeling in chemical data analysis, hyperspectral data analysis, and autoencoder applications in analytical chemistry are then discussed, providing useful examples of the techniques in chemistry applications. Drawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis. Provides an introductory overview of statistical methods for the analysis and interpretation of chemical data Discusses the use of machine learning for recognizing patterns in multidimensional chemical data Identifies common sources of multivariate errors

Multivariate Data Analysis

2002
 |  Experimental design
Multivariate Data Analysis

Author: Kim H. Esbensen

Publisher: Multivariate Data Analysis

ISBN: 8299333032

Category: Experimental design

Page: 622

View: 597

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"Multivariate Data Analysis - in practice adopts a practical, non-mathematical approach to multivariate data analysis. The book's principal objective is to provide a conceptual framework for multivariate data analysis techniques, enabling the reader to apply these in his or her own field. Features: Focuses on the practical application of multivariate techniques such as PCA, PCR and PLS and experimental design. Non-mathematical approach - ideal for analysts with little or no background in statistics. Step by step introduction of new concepts and techniques promotes ease of learning. Theory supported by hands-on exercises based on real-world data. A full training copy of The Unscrambler (for Windows 95, Windows NT 3.51 or later versions) including data sets for the exercises is available. Tutorial exercises based on data from real-world applications are used throughout the book to illustrate the use of the techniques introduced, providing the reader with a working knowledge of modern multivariate data analysis and experimental design. All exercises use The Unscrambler, a de facto industry standard for multivariate data analysis software packages. Multivariate Data Analysis in Practice is an excellent self-study text for scientists, chemists and engineers from all disciplines (non-statisticians) wishing to exploit the power of practical multivariate methods. It is very suitable for teaching purposes at the introductory level, and it can always be supplemented with higher level theoretical literature."Résumé de l'éditeur.

Scientific Data Ranking Methods

2008-11-17
 |  Mathematics
Scientific Data Ranking Methods

Author:

Publisher: Elsevier

ISBN: 0080931936

Category: Mathematics

Page: 224

View: 442

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This volume presents the basic mathematics of ranking methods through a didactic approach and the integration of relevant applications. Ranking methods can be applied in several different fields, including decision support, toxicology, environmental problems, proteomics and genomics, analytical chemistry, food chemistry, and QSAR. . Covers a wide range of applications, from the environment and toxicology to DNA sequencing . Incorporates contributions from renowned experts in the field . Meets the increasing demand for literature concerned with ranking methods and their applications

Design and Analysis in Chemical Research

2000
 |  Science
Design and Analysis in Chemical Research

Author: Roy L. Tranter

Publisher: John Wiley & Sons

ISBN: 9781850759942

Category: Science

Page: 580

View: 442

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Recent years have seen massive changes in the tools and instrumentation available to chemists, in the scale of databases linking the properties of pure materials, solutions or other mixtures to molecular structure, and in the sheer ability of chemists to collect data through automated data acquisition systems. Despite these advances, many chemists still apply only rudimentary data analysis techniques and remain unaware of the advances made in information extraction over the last decade or so. This volume covers the principles of design and analysis in chemical research and development. It is organised in chapters dealing with major activities, and understanding is generated through large numbers of examples and practical applications relating to research and development chemistry. Authors adopt a user-friendly approach, concentrating on principles and interpretation rather than formal derivation and proof. A principal theme is that statistics and chemometrics (which relies on statistics) are essentially extensions of the logical processes used every day by chemists, and that they bring greater understanding of problems more quickly and easily than purely intuitive methods.

Statistical Analysis Methods for Chemists

2007-10-31
 |  Science
Statistical Analysis Methods for Chemists

Author: William P Gardiner

Publisher: Royal Society of Chemistry

ISBN: 9781847551924

Category: Science

Page: 388

View: 596

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Many forms of chemical experimentation generate data needing analysis and interpretation in respect of the goals of the experiment and also the chemical factors which may influence the outcome. Statistical data analysis techniques provide the tools which enable a chemist to assess the information obtained from experiments. Statistical Analysis Methods for Chemists: A Software-based Approach aims to give a broad introduction to practical data analysis, and provides comprehensive coverage of basic statistical principles and reasoning. With practical examples, and integration of software output as the basis of data analysis, this useful book gives unique coverage of the statistical skills and techniques required in modern chemical experimentation. It will prove invaluable to students and researchers alike. Software update information is available from W Gardiner at [email protected] or fax +44 (0)141 331 3608. Please accompany requests for information with details of the software version to be used.

Photochemistry of Organic Compounds

2009-03-23
 |  Science
Photochemistry of Organic Compounds

Author: Petr Klán

Publisher: John Wiley & Sons

ISBN: 9781405190886

Category: Science

Page: 583

View: 219

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Photochemistry of Organic Compounds: From Concepts to Practice provides a hands-on guide demonstrating the underlying principles of photochemistry and, by reference to a range of organic reaction types, its effective use in the synthesis of new organic compounds and in various applications. The book presents a complete and methodical approach to the topic, Working from basic principles, discussing key techniques and studies of reactive intermediates, and illustrating synthetic photochemical procedures. Incorporating special topics and case studies covering various applications of photochemistry in chemistry, environmental sciences, biochemistry, physics, medicine, and industry. Providing extensive references to the original literature and to review articles. Concluding with a chapter on retrosynthetic photochemistry, listing key reactions to aid the reader in designing their own synthetic pathways. This book will be a valuable source of information and inspiration for postgraduates as well as professionals from a wide range of chemical and natural sciences.

Statistical Methods in Analytical Chemistry

2005-03-04
 |  Science
Statistical Methods in Analytical Chemistry

Author: Peter C. Meier

Publisher: John Wiley & Sons

ISBN: 9780471726111

Category: Science

Page: 456

View: 766

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This new edition of a successful, bestselling book continues toprovide you with practical information on the use of statisticalmethods for solving real-world problems in complex industrialenvironments. Complete with examples from the chemical andpharmaceutical laboratory and manufacturing areas, this thoroughlyupdated book clearly demonstrates how to obtain reliable results bychoosing the most appropriate experimental design and dataevaluation methods. Unlike other books on the subject, Statistical Methods inAnalytical Chemistry, Second Edition presents and solves problemsin the context of a comprehensive decision-making process under GMPrules: Would you recommend the destruction of a $100,000 batch ofproduct if one of four repeat determinations barely fails thespecification limit? How would you prevent this from happening inthe first place? Are you sure the calculator you are using istelling the truth? To help you control these situations, the newedition: * Covers univariate, bivariate, and multivariate data * Features case studies from the pharmaceutical and chemicalindustries demonstrating typical problems analysts encounter andthe techniques used to solve them * Offers information on ancillary techniques, including a shortintroduction to optimization, exploratory data analysis, smoothingand computer simulation, and recapitulation of errorpropagation * Boasts numerous Excel files and compiled Visual Basic programs-nostatistical table lookups required! * Uses Monte Carlo simulation to illustrate the variabilityinherent in statistically indistinguishable data sets Statistical Methods in Analytical Chemistry, Second Edition is anexcellent, one-of-a-kind resource for laboratory scientists andengineers and project managers who need to assess data reliability;QC staff, regulators, and customers who want to frame realisticrequirements and specifications; as well as educators looking forreal-life experiments and advanced students in chemistry andpharmaceutical science. From the reviews of Statistical Methods in Analytical Chemistry,First Edition: "This book is extremely valuable. The authors supply many veryuseful programs along with their source code. Thus, the user cancheck the authenticity of the result and gain a greaterunderstanding of the algorithm from the code. It should be on thebookshelf of every analytical chemist."-Applied Spectroscopy "The authors have compiled an interesting collection of data toillustrate the application of statistical methods . . . includingcalibrating, setting detection limits, analyzing ANOVA data,analyzing stability data, and determining the influence of errorpropagation."-Clinical Chemistry "The examples are taken from a chemical/pharmaceutical environment,but serve as convenient vehicles for the discussion of when to usewhich test, and how to make sense out of the results. Whilepractical use of statistics is the major concern, it is put intoperspective, and the reader is urged to use plausibilitychecks."-Journal of Chemical Education "The discussion of univariate statistical tests is one of the morethorough I have seen in this type of book . . . The treatment oflinear regression is also thorough, and a complete set of equationsfor uncertainty in the results is presented . . . The bibliographyis extensive and will serve as a valuable resource for thoseseeking more information on virtually any topic covered in thebook."-Journal of American Chemical Society "This book treats the application of statistics to analyticalchemistry in a very practical manner. [It] integrates PC computingpower, testing programs, and analytical know-how in the context ofgood manufacturing practice/good laboratory practice (GMP/GLP) . ..The book is of value in many fields of analytical chemistry andshould be available in all relevant libraries."-Chemometrics andIntelligent Laboratory Systems

Practical Data Analytics for Innovation in Medicine

2023-04-06
 |  Computers
Practical Data Analytics for Innovation in Medicine

Author: Gary D Miner

Publisher: Academic Press

ISBN: 9780323952750

Category: Computers

Page: 578

View: 937

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Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics. Brings a historical perspective in medical care to discuss both the current status of health care delivery worldwide and the importance of using modern predictive analytics to help solve the health care crisis Provides online tutorials on several predictive analytics systems to help readers apply their knowledge on today’s medical issues and basic research Teaches how to develop effective predictive analytic research and to create decisioning/prescriptive analytic systems to make medical decisions quicker and more accurate