Chemometrics in Excel

A new, full-color, completely updated edition of the key practical guide to chemometrics This new edition of this practical guide on chemometrics, emphasizes the principles and applications behind the main ideas in the field using numerical and graphical examples, which can then be applied to a wide variety of problems in chemistry, biology, chemical engineering, and allied disciplines. Presented in full color, it features expansion of the principal component analysis, classification, multivariate evolutionary signal and statistical distributions sections, and new case studies in metabolomics, as well as extensive updates throughout. Aimed at the large number of users of chemometrics, it includes extensive worked problems and chapters explaining how to analyze datasets, in addition to updated descriptions of how to apply Excel and Matlab for chemometrics. Chemometrics: Data Driven Extraction for Science, Second Edition offers chapters covering: experimental design, signal processing, pattern recognition, calibration, and evolutionary data. The pattern recognition chapter from the first edition is divided into two separate ones: Principal Component Analysis/Cluster Analysis, and Classification. It also includes new descriptions of Alternating Least Squares (ALS) and Iterative Target Transformation Factor Analysis (ITTFA). Updated descriptions of wavelets and Bayesian methods are included. Includes updated chapters of the classic chemometric methods (e.g. experimental design, signal processing, etc.) Introduces metabolomics-type examples alongside those from analytical chemistry Features problems at the end of each chapter to illustrate the broad applicability of the methods in different fields Supplemented with data sets and solutions to the problems on a dedicated website Chemometrics: Data Driven Extraction for Science, Second Edition is recommended for post-graduate students of chemometrics as well as applied scientists (e.g. chemists, biochemists, engineers, statisticians) working in all areas of data analysis.

The third edition of this long-selling introductory textbook and ready reference covers all pertinent topics, from basic statistics via modeling and databases right up to the latest regulatory issues. The experienced and internationally recognized author, Matthias Otto, introduces the statistical-mathematical evaluation of chemical measurements, especially analytical ones, going on to provide a modern approach to signal processing, designing and optimizing experiments, pattern recognition and classification, as well as modeling simple and nonlinear relationships. Analytical databases are equally covered as are applications of multiway analysis, artificial intelligence, fuzzy theory, neural networks, and genetic algorithms. The new edition has 10% new content to cover such recent developments as orthogonal signal correction and new data exchange formats, tree based classification and regression, independent component analysis, ensemble methods and neuro-fuzzy systems. It still retains, however, the proven features from previous editions: worked examples, questions and problems, additional information and brief explanations in the margin.

The book introduces most of the basic tools of chemometrics including experimental design, signal analysis, statistical methods for analytical chemistry and multivariate methods. It then discusses a number of important applications including food chemistry, biological pattern recognition, reaction monitoring, optimisation of processes, medical applications. The book arises from a series of short articles that have been developed over four years on Chemweb (www.chemweb.com).

Financial Applications using Excel Add-in Development in C/C++ is a must-buy book for any serious Excel developer.Excel is the industry standard for financial modelling, providing a number of ways for users to extend the functionality of their own add-ins, including VBA and C/C++. This is the only complete how-to guide and reference book for the creation of high performance add-ins for Excel in C and C++ for users in the finance industry. Steve Dalton explains how to apply Excel add-ins to financial applications with many examples given throughout the book. It also covers the relative strengths and weaknesses of developing add-ins for Excel in VBA versus C/C++, and provides comprehensive code, workbooks and example projects on the accompanying CD-ROM. The impact of Excel 2007’s multi-threaded workbook calculations and large grids on add-in development are fully explored. Financial Applications using Excel Add-in Development in C/C++ features: Extensive example codes in VBA, C and C++, explaining all the ways in which a developer can achieve their objectives. Example projects that demonstrate, from start to finish, the potential of Excel when powerful add-ins can be easily developed. Develops the readers understanding of the relative strengths and weaknesses of developing add-ins for Excel in VBA versus C/C++. A CD-ROM with several thousand lines of example code, numerous workbooks, and a number of complete example projects.

I've worked with simulation in business for over 20 years, and Allman really nails it with this book. I admit that I own his previous book on structured finance cash flows, but I was surprised by what I found in here. He addresses the fundamental questions of how decision makers react to simulations and his read was very much in accordance with what I've experienced myself. When it came to the nuts and bolts of describing the different types of simulation analysis the book becomes incredibly detailed. There is working code and models for a fantastic array of the most common simulation problems. If you're so inclined, the book very carefully steps through the tricky math needed to really understand the theory behind stochastic modeling in finance. If you're preparing models that include any kind of randomization or stochastic modeling component, this book is a must-read, a tremendous value and time-saver. – David Brode of The Brode Group A practical guide to understanding and implementing financial simulation modeling As simulation techniques become more popular among the financial community and a variety of sub-industries, a thorough understanding of theory and implementation is critical for practitioners involved in portfolio management, risk management, pricing, and capital budgeting. Financial Simulation Modeling in Excel contains the information you need to make the most informed decisions possible in your professional endeavors. Financial Simulation Modeling in Excel contains a practical, hands-on approach to learning complex financial simulation methodologies using Excel and VBA as a medium. Crafted in an easy to understand format, this book is suitable for anyone with a basic understanding of finance and Excel. Filled with in-depth insights and expert advice, each chapter takes you through the theory behind a simulation topic and the implementation of that same topic in Excel/VBA in a step-by-step manner. Organized in an easy-to-follow fashion, this guide effectively walks you through the process of creating and implementing risk models in Excel A companion website contains all the Excel models risk experts and quantitative analysts need to practice and confirm their results as they progress Keith Allman is the author of other successful modeling books, including Corporate Valuation Modeling and Modeling Structured Finance Cash Flows with Microsoft Excel Created for those with some background in finance and experience in Excel, this reliable resource shows you how to effectively perform sound financial simulation modeling, even if you've yet to do extensive modeling up to this point in your professional or academic career.

A practical and methodological approach to the statistical logic of biostatistics in the field of health research Focusing on a basic understanding of the methods and analyses in health research, Introduction to Biostatistical Applications in Health Research with Microsoft® Office Excel® provides statistical concepts for interpreting results using Excel. The book emphasizes the application of methods and presents the most common methodological procedures in health research, which includes multiple regression, ANOVA, ANCOVA, logistic regression, Cox regression, stratified analysis, life table analysis, and nonparametric parallels. The book is constructed around a flowchart that outlines the appropriate circumstances for selecting a method to analyze a specific set of data. Beginning with an introduction to the foundational methods of statistical logic before moving on to more complex methods, Introduction to Biostatistical Applications in Health Research with Microsoft® Office Excel® also includes: Detailed discussions of how knowledge and skills in health research have been integrated with biostatistical methods Numerous examples with clear explanations that use mostly real-world health research data in order to provide a better understanding of the practical applications Implements Excel graphic representations throughout to help readers evaluate and analyze individual results An appendix with basic information on how to use Excel A companion website with additional Excel files, data sets, and homework problems as well as an Instructor’s Solutions Manual Introduction to Biostatistical Applications in Health Research with Microsoft® Office Excel® is an excellent textbook for upper-undergraduate and graduate-level courses in biostatistics and public health. In addition, the book is an appropriate reference for both health researchers and professionals.

Reviews from the First Edition: «Excel® for Chemists should be part of any academic library offering courses and programs in chemistry. There is no other book on the market that deals so thoroughly with the application of Excel for analyzing chemical data. Highly recommended, for upper-division undergraduates through professionals.» -Choice «I highly recommend this book; treat yourself to it; assign it to a class; give it as a gift.» -The Nucleus Chemists across all subdisciplines use Excel to record data in tabular form, but few have learned to take full advantage of the scientific calculating power within this program. Excel is capable of helping chemists process, analyze, and present scientific data, from the relatively simple to the highly complex. Excel® for Chemists, Second Edition has been revised and updated, not only to take into account the changes that were made in Excel, but also to incorporate an abundance of new examples. Arranged in a user-friendly format, this book contains illustrations and examples of chemical applications, useful «How to» boxes outlining how to accomplish complex tasks in Excel, and step-by-step instructions for programming Excel to automate repetitive data-processing tasks. In addition, tips are provided to speed, simplify, and improve your use of Excel. Included is a CD-ROM, usable in either Macintosh or IBM/Windows environments with many helpful spreadsheet templates, macros, and other tools. Entirely new chapters contained in this Second Edition feature: Array formulas covered in depth in a separate chapter, along with a comprehensive review of using arrays in VBA How to create a worksheet with controls, such as option buttons, check boxes, or a list box An extensive list of shortcut keys-over 250 for Macintosh or PC-is provided in the appendix Whether as a text for students or as a reference for chemical professionals in industry, academia, or government, Excel® for Chemists, Second Edition provides a valuable resource for using Excel to manage various chemical calculations.

Provides a step-by-step approach to statistical procedures to analyze data and conduct research, with detailed sections in each chapter explaining SPSS® and Excel® applications This book identifies connections between statistical applications and research design using cases, examples, and discussion of specific topics from the social and health sciences. Researched and class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations for both the novice and professional alike to understand the fundamental statistical practices for organizing, analyzing, and drawing conclusions from research data in their field. The book begins with an introduction to descriptive and inferential statistics and then acquaints readers with important features of statistical applications (SPSS and Excel) that support statistical analysis and decision making. Subsequent chapters treat the procedures commonly employed when working with data across various fields of social science research. Individual chapters are devoted to specific statistical procedures, each ending with lab application exercises that pose research questions, examine the questions through their application in SPSS and Excel, and conclude with a brief research report that outlines key findings drawn from the results. Real-world examples and data from social and health sciences research are used throughout the book, allowing readers to reinforce their comprehension of the material. Using Statistics in the Social and Health Sciences with SPSS® and Excel® includes: • Use of straightforward procedures and examples that help students focus on understanding of analysis and interpretation of findings • Inclusion of a data lab section in each chapter that provides relevant, clear examples • Introduction to advanced statistical procedures in chapter sections (e.g., regression diagnostics) and separate chapters (e.g., multiple linear regression) for greater relevance to real-world research needs Emphasizing applied statistical analyses, this book can serve as the primary text in undergraduate and graduate university courses within departments of sociology, psychology, urban studies, health sciences, and public health, as well as other related departments. It will also be useful to statistics practitioners through extended sections using SPSS® and Excel® for analyzing data. Martin Lee Abbott, PhD, is Professor of Sociology at Seattle Pacific University, where he has served as Executive Director of the Washington School Research Center, an independent research and data analysis center funded by the Bill & Melinda Gates Foundation. Dr. Abbott has held positions in both academia and industry, focusing his consulting and teaching in the areas of statistical procedures, program evaluation, applied sociology, and research methods. He is the author of Understanding Educational Statistics Using Microsoft Excel® and SPSS®, The Program Evaluation Prism: Using Statistical Methods to Discover Patterns, and Understanding and Applying Research Design, also from Wiley.

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A practical introductory guide to optical design covering geometrical optics, simple wave-optics and diffraction, using Excel software • explains practical calculation methods for designing optical systems with fully worked-out examples and avoiding complex mathematical methods • includes practical calculations for ray tracing, laser beam (Gaussian beam) focusing, and diffraction calculations; the ray tracing and the diffraction calculations are done by using the VBA program which Excel provides as a supporting tool • describes basic optical theory and application methods, and provides readers with calculation methods for designing laser optical systems with numerous practical calculation examples. After finishing the book, even inexperienced readers should have the ability to design laser optical systems • covers large areas of geometrical optics and diffraction theory, providing a good overview and reference for beginners or non-specialist engineers • accompanied by a website including password protected electronic files