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Analytics for the Internet of Things (IoT)
by Andrew MinteerThis book targets developers, IoT professionals, and those in the field of data science who are trying to solve business problems through IoT devices and would like to analyze IoT data. IoT enthusiasts, managers, and entrepreneurs who would like to make the most of IoT will find this equally useful. A prior knowledge of IoT would be helpful but is not necessary. Some prior programming experience would be useful
Analytics for the Sharing Economy: Mathematics, Engineering and Business Perspectives
by Giovanni Russo Emanuele Crisostomi Robert Shorten Bissan Ghaddar Florian Häusler Joe Naoum-SawayaThe book provides an encompassing overview of all aspects relating to the sharing economy paradigm in different fields of study, and shows the ongoing research efforts in filling previously identified gaps in understanding in this area. Control and optimization analytics for the sharing economy explores bespoke analytics, tools, and business models that can be used to help design collaborative consumption services (the shared economy). It provides case studies of collaborative consumption in the areas of energy and mobility.The contributors review successful examples of sharing systems, and explore the theory for designing effective and stable shared-economy models. They discuss recent innovations in and uses of shared economy models in niche areas, such as energy and mobility. Readers learn the scientific challenging issues associated with the realization of a sharing economy. Conceptual and practical matters are examined, and the state-of-the-art tools and techniques to address such applications are explained. The contributors also show readers how topical problems in engineering, such as energy consumption in power grids, or bike sharing in transportation networks, can be formulated and solved from a general collaborative consumption perspective. Since the book takes a mathematical perspective to the topic, researchers in business, computer science, optimization and control find it useful. Practitioners also use the book as a point of reference, as it explores and investigates the analytics behind economy sharing.
Analytics in a Big Data World
by Bart BaesensThe guide to targeting and leveraging business opportunities using big data & analyticsBy leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments.The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic.Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and governmentContains an overview of the visionary ideas and current developments on the strategic use of analytics for businessCovers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysisFor organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.
Analytics in Finance and Risk Management (Information Technology, Management and Operations Research Practices)
by Nga Thi Hong Nguyen Shivani Agarwal Ewa ZiembaThis book presents contemporary issues and challenges in finance and risk management in a time of rapid transformation due to technological advancements. It includes research articles based on financial and economic data and intends to cover the emerging role of analytics in financial management, asset management, and risk management. Analytics in Finance and Risk Management covers statistical techniques for data analysis in finance It explores applications in finance and risk management, covering empirical properties of financial systems. It addresses data science involving the study of statistical and computational models and includes basic and advanced concepts. The chapters incorporate the latest methodologies and challenges facing financial and risk management and illustrate related issues and their implications in the real world. The primary users of this book will include researchers, academicians, postgraduate students, professionals in engineering and business analytics, managers, consultants, and advisors in IT firms, financial markets, and services domains.
Analytics in Healthcare: An Introduction (HIMSS Book Series)
by Raymond A. GensingerThe editors of the HIMSS Books' best-seller Health: From Smartphones to Smart Systems have returned to deliver an expansive survey of the initiatives, innovators, and technologies driving the patient-centered mobile healthcare revolution. mHealth Innovation: Best Practices from the Mobile Frontier explores the promise of mHealth as a balance between emerging technologies and process innovations leading to improved outcomes-with the ultimate aim of creating a patient-centered and consumer-driven healthcare ecosystem. Examining the rapidly changing mobile healthcare environment from myriad perspectives, the book includes a comprehensive survey of the current-state ecosystem-app development, interoperability, security, standards, organizational and governmental policy, innovation, next-generation solutions, and mBusiness-and 20 results-driven, world-spanning case studies covering behavior change, patient engagement, patient-provider decision making, mobile gaming, mobile prescription therapy, home monitoring, mobile-to-mobile online delivery, access to care, app certification and quality evaluations, mixed media campaigns, and much more.
Analytics in Healthcare: A Practical Introduction (SpringerBriefs in Health Care Management and Economics)
by Christo El Morr Hossam Ali-HassanThis book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes multiple examples of their applications in the field. The book also identifies practical challenges that fuel the need for analytics in healthcare as well as the solutions to address these problems. In the healthcare field, professionals have access to vast amount of data in the form of staff records, electronic patient record, clinical findings, diagnosis, prescription drug, medical imaging procedure, mobile health, resources available, etc. Managing the data and analyzing it to properly understand it and use it to make well-informed decisions can be a challenge for managers and health care professionals. A new generation of applications, sometimes referred to as end-user analytics or self-serve analytics, are specifically designed for non-technical users such as managers and business professionals. The ability to use these increasingly accessible tools with the abundant data requires a basic understanding of the core concepts of data, analytics, and interpretation of outcomes. This book is a resource for such individuals to demystify and learn the basics of data management and analytics for healthcare, while also looking towards future directions in the field.
Analytics in Smart Tourism Design: Concepts and Methods (Tourism on the Verge)
by Daniel R. Fesenmaier Zheng XiangThis book presents cutting edge research on the development of analytics in travel and tourism. It introduces new conceptual frameworks and measurement tools, as well as applications and case studies for destination marketing and management. It is divided into five parts: Part one on travel demand analytics focuses on conceptualizing and implementing travel demand modeling using big data. It illustrates new ways to identify, generate and utilize large quantities of data in tourism demand forecasting and modeling. Part two focuses on analytics in travel and everyday life, presenting recent developments in wearable computers and physiological measurement devices, and the implications for our understanding of on-the-go travelers and tourism design. Part three embraces tourism geoanalytics, correlating social media and geo-based data with tourism statistics. Part four discusses web-based and social media analytics and presents the latest developments in utilizing user-generated content on the Internet to understand a number of managerial problems. The final part is a collection of case studies using web-based and social media analytics, with examples from the Sochi Olympics on Twitter, leveraging online reviews in the hotel industry, and evaluating destination communications and market intelligence with online hotel reviews. The chapters in this section collectively describe a range of different approaches to understanding market dynamics in tourism and hospitality.
Analytics, Innovation, and Excellence-Driven Enterprise Sustainability (Palgrave Studies in Democracy, Innovation, and Entrepreneurship for Growth)
by Elias G. Carayannis Stavros SindakisThis book offers a unique view of how innovation and competitiveness improve when organizations establish alliances with partners who have strong capabilities and broad social capital, allowing them to create value and growth as well as technological knowledge and legitimacy through new knowledge resources. Organizational intelligence integrates the technology variable into production and business systems, establishing a basis to advance decision-making processes. When strategically integrated, these factors have the power to promote enterprise resilience, robustness, and sustainability. This book provides a unique perspective on how knowledge, information, and data analytics create opportunities and challenges for sustainable enterprise excellence. It also shows how the value of digital technology at both personal and industrial levels leads to new opportunities for creating experiences, processes, and organizational forms that fundamentally reshape organizations.
The Analytics Lifecycle Toolkit: A Practical Guide for an Effective Analytics Capability (Wiley and SAS Business Series)
by Gregory S. NelsonAn evidence-based organizational framework for exceptional analytics team results The Analytics Lifecycle Toolkit provides managers with a practical manual for integrating data management and analytic technologies into their organization. Author Gregory Nelson has encountered hundreds of unique perspectives on analytics optimization from across industries; over the years, successful strategies have proven to share certain practices, skillsets, expertise, and structural traits. In this book, he details the concepts, people and processes that contribute to exemplary results, and shares an organizational framework for analytics team functions and roles. By merging analytic culture with data and technology strategies, this framework creates understanding for analytics leaders and a toolbox for practitioners. Focused on team effectiveness and the design thinking surrounding product creation, the framework is illustrated by real-world case studies to show how effective analytics team leadership works on the ground. Tools and templates include best practices for process improvement, workforce enablement, and leadership support, while guidance includes both conceptual discussion of the analytics life cycle and detailed process descriptions. Readers will be equipped to: Master fundamental concepts and practices of the analytics life cycle Understand the knowledge domains and best practices for each stage Delve into the details of analytical team processes and process optimization Utilize a robust toolkit designed to support analytic team effectiveness The analytics life cycle includes a diverse set of considerations involving the people, processes, culture, data, and technology, and managers needing stellar analytics performance must understand their unique role in the process of winnowing the big picture down to meaningful action. The Analytics Lifecycle Toolkit provides expert perspective and much-needed insight to managers, while providing practitioners with a new set of tools for optimizing results.
Analytics, Machine Learning, and Artificial Intelligence: Second Analytics Global Conference, AGC 2024, Kolkata, India, March 6–7, 2024, Revised Selected Papers (Communications in Computer and Information Science #2224)
by Suparna Dhar Sanjay Goswami Dinesh Kumar Unni Krishnan Indranil Bose Rameshwar Dubey Chandan MazumdarThis book constitutes the refereed proceedings of the Second Analytics Global Conference on Analytics, Machine Learning, and Artificial Intelligence, AGC 2024, held in Kolkata, India, during March 6-7, 2024. The 15 full papers and 3 short papers presented in these proceedings were carefully reviewed and selected from 60 submissions. The papers are organized in these topical sections: applications of analytics in business; analytics methods, tools & techniques.
Analytics Modeling in Reliability and Machine Learning and Its Applications (Springer Series in Reliability Engineering)
by Hoang PhamThis book presents novel research and application chapters on topics in reliability, statistics, and machine learning. It has an emphasis on analytical models and techniques and practical applications in reliability engineering, data science, manufacturing, health care, and industry using machine learning, AI, optimization, and other computational methods. Today, billions of people are connected to each other through their mobile devices. Data is being collected and analysed more than ever before. The era of big data through machine learning algorithms, statistical inference, and reliability computing in almost all applications has resulted in a dramatic shift in the past two decades. Data analytics in business, finance, and industry is vital. It helps organizations and business to achieve better results and fact-based decision-making in all aspects of life. The book offers a broad picture of current research on the analytics modeling and techniques and its applications in industry. Topics include: l Reliability modeling and methods. l Software reliability engineering. l Maintenance modeling and policies. l Statistical feature selection. l Big data modeling. l Machine learning: models and algorithms. l Data-driven models and decision-making methods. l Applications and case studies in business, health care, and industrial systems. Postgraduates, researchers, professors, scientists, engineers, and practitioners in reliability engineering and management, machine learning engineering, data science, operations research, industrial and systems engineering, statistics, computer science and engineering, mechanical engineering, and business analytics will find in this book state-of-the-art analytics, modeling and methods in reliability and machine learning.
The Analytics of Uncertainty and Information Second Edition
by Sushil Bikhchandani Jack Hirshleifer John G. Riley Sushil Bikhchandani Jack HirshleiferThere has been explosive progress in the economic theory of uncertainty and information in the past few decades. This subject is now taught not only in departments of economics but also in professional schools and programs oriented toward business, government and administration, and public policy. This book attempts to unify the subject matter in a simple, accessible manner. Part I of the book focuses on the economics of uncertainty; Part II examines the economics of information. This revised and updated second edition places a greater focus on game theory. New topics include posted-price markets, mechanism design, common-value auctions, and the one-shot deviation principle for repeated games.
Analytics Optimization with Columnstore Indexes in Microsoft SQL Server: Optimizing OLAP Workloads
by Edward PollackMeet the challenge of storing and accessing analytic data in SQL Server in a fast and performant manner. This book illustrates how columnstore indexes can provide an ideal solution for storing analytic data that leads to faster performing analytic queries and the ability to ask and answer business intelligence questions with alacrity. The book provides a complete walk through of columnstore indexing that encompasses an introduction, best practices, hands-on demonstrations, explanations of common mistakes, and presents a detailed architecture that is suitable for professionals of all skill levels. With little or no knowledge of columnstore indexing you can become proficient with columnstore indexes as used in SQL Server, and apply that knowledge in development, test, and production environments. This book serves as a comprehensive guide to the use of columnstore indexes and provides definitive guidelines. You will learn when columnstore indexes should be used, and the performance gains that you can expect. You will also become familiar with best practices around architecture, implementation, and maintenance. Finally, you will know the limitations and common pitfalls to be aware of and avoid.As analytic data can become quite large, the expense to manage it or migrate it can be high. This book shows that columnstore indexing represents an effective storage solution that saves time, money, and improves performance for any applications that use it. You will see that columnstore indexes are an effective performance solution that is included in all versions of SQL Server, with no additional costs or licensing required. What You Will LearnImplement columnstore indexes in SQL ServerKnow best practices for the use and maintenance of analytic data in SQL ServerUse metadata to fully understand the size and shape of data stored in columnstore indexesEmploy optimal ways to load, maintain, and delete data from large analytic tablesKnow how columnstore compression saves storage, memory, and timeUnderstand when a columnstore index should be used instead of a rowstore indexBe familiar with advanced features and analyticsWho This Book Is ForDatabase developers, administrators, and architects who are responsible for analytic data, especially for those working with very large data sets who are looking for new ways to achieve high performance in their queries, and those with immediate or future challenges to analytic data and query performance who want a methodical and effective solution
Analytics, Policy, and Governance
by Benjamin Ginsberg Jennifer Bachner Kathryn Wagner HillThe first available textbook on the rapidly growing and increasingly important field of government analytics This first textbook on the increasingly important field of government analytics provides invaluable knowledge and training for students of government in the synthesis, interpretation, and communication of "big data," which is now an integral part of governance and policy making. Integrating all the major components of this rapidly growing field, this invaluable text explores the intricate relationship of data analytics to governance while providing innovative strategies for the retrieval and management of information.
The Analytics Process: Strategic and Tactical Steps
by Eduardo RodriguezThis book is about the process of using analytics and the capabilities of analytics in today’s organizations. Cutting through the buzz surrounding the term analytics and the overloaded expectations about using analytics, the book demystifies analytics with an in-depth examination of concepts grounded in operations research and management science. Analytics as a set of tools and processes is only as effective as: The data with which it is working The human judgment applying the processes and understanding the output of these processes. For this reason, the book focuses on the analytics process. What is intrinsic to analytics’ real organizational impact are the careful application of tools and the thoughtful application of their outcomes. This work emphasizes analytics as part of a process that supports decision-making within organizations. It wants to debunk overblown expectations that somehow analytics outputs or analytics as applied to other concepts, such as Big Data, are the be-all and end-all of the analytics process. They are, instead, only a step within a holistic and critical approach to management thinking that can create real value for an organization. To develop this holistic approach, the book is divided into two sections that examine concepts and applications. The first section makes the case for executive management taking a holistic approach to analytics. It draws on rich research in operations and management science that form the context in which analytics tools are to be applied. There is a strong emphasis on knowledge management concepts and techniques, as well as risk management concepts and techniques. The second section focuses on both the use of the analytics process and organizational issues that are required to make the analytics process relevant and impactful.
The Analytics Revolution
by Bill FranksLead your organization into the industrial revolution of analytics with The Analytics RevolutionThe topics of big data and analytics continue to be among the most discussed and pursued in the business world today. While a decade ago many people still questioned whether or not data and analytics would help improve their businesses, today virtually no one questions the value that analytics brings to the table. The Analytics Revolution focuses on how this evolution has come to pass and explores the next wave of evolution that is underway. Making analytics operational involves automating and embedding analytics directly into business processes and allowing the analytics to prescribe and make decisions. It is already occurring all around us whether we know it or not.The Analytics Revolution delves into the requirements for laying a solid technical and organizational foundation that is capable of supporting operational analytics at scale, and covers factors to consider if an organization is to succeed in making analytics operational. Along the way, you'll learn how changes in technology and the business environment have led to the necessity of both incorporating big data into analytic processes and making them operational. The book cuts straight through the considerable marketplace hype and focuses on what is really important. The book includes:An overview of what operational analytics are and what trends lead us to themTips on structuring technology infrastructure and analytics organizations to succeedA discussion of how to change corporate culture to enable both faster discovery of important new analytics and quicker implementation cycles of what is discoveredGuidance on how to justify, implement, and govern operational analyticsThe Analytics Revolution gives you everything you need to implement operational analytic processes with big data.
The Analytics Revolution in Higher Education: Big Data, Organizational Learning, and Student Success
by Randy L. Swing Jonathan S. Gagliardi Amelia Parnell Julia Carpenter-HubinCo-published with and In this era of “Big Data,” institutions of higher education are challenged to make the most of the information they have to improve student learning outcomes, close equity gaps, keep costs down, and address the economic needs of the communities they serve at the local, regional, and national levels. This book helps readers understand and respond to this “analytics revolution,” examining the evolving dynamics of the institutional research (IR) function, and the many audiences that institutional researchers need to serve.Internally, there is a growing need among senior leaders, administrators, faculty, advisors, and staff for decision analytics that help craft better resource strategies and bring greater efficiencies and return-on-investment for students and families. Externally, state legislators, the federal government, and philanthropies demand more forecasting and more evidence than ever before. These demands require new and creative responses, as they are added to previous demands, rather than replacing them, nor do they come with additional resources to produce the analysis to make data into actionable improvements. Thus the IR function must become that of teacher, ensuring that data and analyses are accurate, timely, accessible, and compelling, whether produced by an IR office or some other source. Despite formidable challenges, IR functions have begun to leverage big data and unlock the power of predictive tools and techniques, contributing to improved student outcomes.
Analytics Stories: Using Data to Make Good Things Happen
by Wayne L. WinstonInform your own analyses by seeing how one of the best data analysts in the world approaches analytics problems Analytics Stories: How to Make Good Things Happen is a thoughtful, incisive, and entertaining exploration of the application of analytics to real-world problems and situations. Covering fields as diverse as sports, finance, politics, healthcare, and business, Analytics Stories bridges the gap between the oft inscrutable world of data analytics and the concrete problems it solves. Distinguished professor and author Wayne L. Winston answers questions like: Was Liverpool over Barcelona the greatest upset in sports history? Was Derek Jeter a great infielder What's wrong with the NFL QB rating? How did Madoff keep his fund going? Does a mutual fund’s past performance predict future performance? What caused the Crash of 2008? Can we predict where crimes are likely to occur? Is the lot of the American worker improving? How can analytics save the US Republic? The birth of evidence-based medicine: How did James Lind know citrus fruits cured scurvy? How can I objectively compare hospitals? How can we predict heart attacks in real time? How does a retail store know if you're pregnant? How can I use A/B testing to improve sales from my website? How can analytics help me write a hit song? Perfect for anyone with the word “analyst” in their job title, Analytics Stories illuminates the process of applying analytic principles to practical problems and highlights the potential pitfalls that await careless analysts.
Analytics the Right Way: A Business Leader's Guide to Putting Data to Productive Use
by Tim Wilson Joe SutherlandCLEAR AND CONCISE TECHNIQUES FOR USING ANALYTICS TO DELIVER BUSINESS IMPACT AT ANY ORGANIZATION Organizations have more data at their fingertips than ever, and their ability to put that data to productive use should be a key source of sustainable competitive advantage. Yet, business leaders looking to tap into a steady and manageable stream of “actionable insights” often, instead, get blasted with a deluge of dashboards, chart-filled slide decks, and opaque machine learning jargon that leaves them asking, “So what?” Analytics the Right Way is a guide for these leaders. It provides a clear and practical approach to putting analytics to productive use with a three-part framework that brings together the realities of the modern business environment with the deep truths underpinning statistics, computer science, machine learning, and artificial intelligence. The result: a pragmatic and actionable guide for delivering clarity, order, and business impact to an organization’s use of data and analytics. The book uses a combination of real-world examples from the authors’ direct experiences—working inside organizations, as external consultants, and as educators—mixed with vivid hypotheticals and illustrations—little green aliens, petty criminals with an affinity for ice cream, skydiving without parachutes, and more—to empower the reader to put foundational analytical and statistical concepts to effective use in a business context.
Analytics und Artificial Intelligence: Datenprojekte mehrwertorientiert, agil und nachhaltig planen und umsetzen
by Ramona Greiner David Berger Matthias BöckDie Autoren zeigen in diesem Buch, wie man für eigene Data-Science-Projekte mit Data Analytics und AI einen echten (Mehr-)Wert schafft. Sie entwickeln einen Leitfaden, mit dem Sie Ihre Datenanalyse systematisch, agil und nutzer:innenzentriert aufbauen und betreiben können. Zunächst machen die Autoren klar, wie wichtig es ist zu Beginn Ihrer Analytics-Projekte die für Ihr Geschäftsmodell richtigen und wertstiftenden Fragen zu stellen. Im Anschluss erläutern sie, wie Sie Technologien und Daten so einsetzen, dass sie einen echten Mehrwert erzeugen können. Schließlich zeigen sie, wie Sie die Projekte effektiv, effizient und gewinnbringend umsetzen können. Das Fundament dafür bilden agile Methoden und Design Thinking, die die Autoren für alltägliche Analytics- und Data-Science-Projekte überführt und adaptiert haben.Mit zahlreichen Beispielen und Erfahrungen aus Daten-, Web- und Digital-Analytics-Projekten sowie zwei realen Beispielen, wie man von der Idee und dem Auftrag zum Prototypen kommt. Aus dem Inhalt Agile Basics: Agile Prinzipien und ErfolgsfaktorenVom Design Thinking zum Data Thinking – wie Design Thinking Datenprojekte besser machtArtificial Intelligence – wie Künstliche Intelligenz mehrwertorientiert in Data Analytics eingesetzt werden kannEthische, rechtliche und ökologische Implikationen – wie Data Analytics und AI doch kein Schreckgespenst werdenDer Data Value Loop - Datenmehrwert agil und nutzer:innenzentriertAnalytics in der Praxis – von der Konzeption über Tracking und Reporting bis zum Arbeitsmeeting im AlltagAI in der Praxis - Data Science und Agile, geht das überhaupt zusammen? Zwei exemplarische ProjektdurchführungenGlossar
Analytische Biochemie: Eine praktische Einfuhrung in das Messen mit Biomolekulen
by Ulla Wollenberger Reinhard Renneberg Frank F. Bier Frieder W. SchellerZur Lösung analytischer Fragestellungen wird in der Biotechnologie, der Lebensmittel- und Umweltanalytik sowie der klinischen und pharmazeutischen Chemie neben der instrumentellen Analytik immer häufiger auf bioanalytische Methoden zurückgegriffen. Diese beruhen z. B. auf dem Einsatz von Enzymen, Nukleinsäuren oder Antikörpern. Dazu bietet das Buch eine praktische Einführung in die qualitative und quantitative Analytik mit biochemischen Reagenzien, die sowohl für das Studium wie für die Weiterbildung im Beruf geeignet ist. Die Autoren schlagen eine Brücke von den theoretischen Grundlagen hin zu den praktischen Anwendungen. Dem vertieften Verständnis dient die Beschreibung erprobter Praktikumsversuche. Die Autoren gehören zu einer der weltweit führenden Forschungsgruppen auf diesem Gebiet, lassen aber auch ihre langjährige Lehrerfahrung in dieses neue Buch einfließen.
Analytische Chemie
by Matthias OttoDer "Otto" hat sich zu einem Standardwerk für Studenten der Chemie, Pharmazie, Lebensmittelchemie und anderer chemischer Disziplinen entwickelt, das auch von Nicht-Chemikern und Chemieingenieuren wegen seines didaktischen Aufbaus und seiner klaren Darstellung geschätzt wird. In fünfter, nochmals aktualisierter und um neueste Analysemethoden ergänzter Auflage, wird das gesamte Analytik-Wissen auf Bachelor-Niveau dargestellt. Mit dem Blick für das Wesentliche erklärt der Autor, worauf es bei den vielen heute gebräuchlichen Analysemethoden wirklich ankommt. Von den Grundlagen der qualitativen und quantitativen Analyse bis zu modernen Hochdurchsatz-Analysegeräten und der Qualitätssicherung wird die gesamte Bandbreite der modernen Analytik vorgestellt. Die fünfte Auflage bietet noch mehr Aufgaben und Lösungen zur Selbstkontrolle, außerdem zahlreiche Beispielrechnungen. Die Begriffe und Konstanten sind nach harmonisierten IUPAC-Definitionen aktualisiert. Eine blaue Schmuckfarbe wird im Buch verwendet, um einen noch effizienteren Lernprozess zu ermöglichen.
Analytische Chemie: Grundlagen, Methoden und Praxis
by Georg Schwedt Oliver J. Schmitz Torsten C. SchmidtAlle relevanten Aspekte der Analytischen Chemie werden in diesem Lehrbuch, das gleichzeitig auch als Referenz fur Praktiker dient, umfassend und klar auf den Punkt gebracht. Das Autorenteam wird durch zwei aktive und international bekannte Professoren verstarkt; dies sorgt fur frischen Wind, gleichzeitig wird der didaktisch ausgefeilte Stil der Vorauflagen beibehalten. Von der Analysenstrategie zur Probenvorbereitung, von der Ma?analyse uber spektroskopische und chromatographische Methoden bis zur Automatisierung - DAS Lehrbuch fur alle, die sich mit Analytischer Chemie beschaftigen.
Analytische Chemie für Dummies (Für Dummies)
by Ulf RitgenDie Analytik ist zwar ein grundlegendes Thema innerhalb der Chemie, hat es aber ganz schön in sich. Aber keine Sorge, Ulf Ritgen erklärt Ihnen in diesem Buch was Sie zur Analytischen Chemie Wissen sollten. Wie erhält man eigentlich analytische Infos? Welche Standards gibt es? Und wie sollte man überhaupt mit den Stoffgemischen umgehen? All diese Grundlagen werden ausführlich erläutert. Aber auch die Anwendungsgebiete und Methoden kommen keinesfalls zu kurz. Egal ob Gravimetrie, Titration, Fällung oder Konduktometrie, endlich wird alles verständlich erklärt. Jetzt können Prüfung und Praktikum kommen!
Analytische Chemie I
by Ulf RitgenDas Arbeitsbuch führt durch das erfolgreiche Werk Harris, Lehrbuch der Quantitativen Analyse und ist vor allem für das Selbststudium konzipiert. In fünf Teilen werden die Vorlesungsinhalte der Analytischen Chemie zusammengefasst und anhand ausgewählter Beispiele erläutert. Grundbegriffe der Analytik werden ebenso dargelegt wie das Prinzip und die verschiedenen Techniken der Maßanalyse und der Chromatographie. Anhand von UV/VIS-, Infrarot- und Raman-Spektroskopie wird die Untersuchung molekular vorliegender Verbindungen erklärt, mit ausgewählten Techniken der Atomspektroskopie findet die Einführung in die Grundlagen der Analytik ihren Abschluss. Dabei wird immer wieder auf essenzielle Abschnitte und Abbildungen des Lehrbuches verwiesen, was das selbstständige Lernen der Grundlagen der Analytischen Chemie erleichtert.Leicht lesbar führt das Buch in die Grundlagen und die wichtigsten Techniken der Analytischen Chemie ein; es richtet sich an Studierende im Grundstudium der Chemie oder verwandter naturwissenschaftlicher Fächer. Dabei wird immer wieder auf die aus Lehrveranstaltungen der Allgemeinen Chemie bekannten Grundlagen Rückbezug genommen, sodass die Zusammenhänge zwischen bereits Bekanntem und Neuem sofort erkenntlich werden. Das Lernen mit diesem Arbeitsbuch ist in einem Fernstudiengang Chemie erprobt und erleichtert die Vorbereitung auf Modulprüfungen der Analytischen Chemie.