This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book 'Multivariate Time Series With Linear State Space Structure', by the same author, if they require more details.

Customer survey studies deals with customers, consumers and user satisfaction from a product or service. In practice, many of the customer surveys conducted by business and industry are analyzed in a very simple way, without using models or statistical methods. Typical reports include descriptive statistics and basic graphical displays. As demonstrated in this book, integrating such basic analysis with more advanced tools, provides insights on non-obvious patterns and important relationships between the survey variables. This knowledge can significantly affect the conclusions derived from a survey.

Key features: Provides an integrated, case-studies based approach to analysing customer survey data.Presents a general introduction to customer surveys, within an organization's business cycle.Contains classical techniques with modern and non standard tools.Focuses on probabilistic techniques from the area of statistics/data analysis and covers all major recent developments.Accompanied by a supporting website containing datasets and R scripts.

Customer survey specialists, quality managers and market researchers will benefit from this book as well as specialists in marketing, data mining and business intelligence fields.

The book is aimed at Project Management Professionals who are casual or new users and understand the software basics but require a short and snappy guide. It is the sort of book that may be read without a computer on the bus, train or plane. This book quickly gets down to the issues that many people grapple with when trying to use some of the more advanced features of the software and enlightens readers on the traps that some users fall into and how to avoid them. It demonstrates how the software ticks and explains some tricks that may be used to become more productive with the software and generate better schedules. Suitable for people who understand the basics of Microsoft Project but want a short guide to give them insight into the less intuitive features of the software. It is packed with screen shots, constructive tips and is written in plain English. The book is based on the Microsoft Project 365 and 2021 but may be used with earlier versions of Microsoft Project as this book points out the differences where appropriate. The book picks out many of the key aspects from the author's exiting books and adds a substantial amount of new and original text to produce a pocket guide that omits describing the intuitive and obvious functions and concentrates on the issues that many users get stuck on or find hard to understand.

Conquer the complexities of this open source statistical language

R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context. Both students and workers in fields that require extensive statistical analysis will find this book helpful as they learn to use R for simple summary statistics, hypothesis testing, creating graphs, regression, and much more. It covers formula notation, complex statistics, manipulating data and extracting components, and rudimentary programming.R, the open source statistical language increasingly used to handle statistics and produces publication-quality graphs, is notoriously complex This book makes R easier to understand through the use of simple statistical examples, teaching the necessary elements in the context in which R is actually usedCovers getting started with R and using it for simple summary statistics, hypothesis testing, and graphsShows how to use R for formula notation, complex statistics, manipulating data, extracting components, and regressionProvides beginning programming instruction for those who want to write their own scripts

"Beginning R" offers anyone who needs to perform statistical analysis the information necessary to use R with confidence.

Introduction to Chemical Engineering Analysis Using Mathematica, Second Edition reviews the processes and designs used to manufacture, use, and dispose of chemical products using Mathematica, one of the most powerful mathematical software tools available for symbolic, numerical, and graphical computing. Analysis and computation are explained simultaneously. The book covers the core concepts of chemical engineering, ranging from the conservation of mass and energy to chemical kinetics. The text also shows how to use the latest version of Mathematica, from the basics of writing a few lines of code through developing entire analysis programs. This second edition has been fully revised and updated, and includes analyses of the conservation of energy, whereas the first edition focused on the conservation of mass and ordinary differential equations.

What is SAP Business Technology Platform, and what does it offer your organization? Answer these questions and more with this introduction! See how SAP BTP serves as your complete technical foundation and learn about its capabilities for application development, integration, data management, analytics, and more. Identify business use cases and follow practical examples that show how to use SAP BTP's portfolio to its full potential. Envision how SAP BTP enhances your business!1. In this book, you'll learn about: a. Architecture Learn about enterprise architecture design. Build your IT strategy with SAP BTP by walking through design patterns and planning your development approach. b. Technologies and ServicesExplore the complete SAP BTP portfolio. See how SAP BTP supports database management, system and process integration, analytics, DevOps, and more as your unified technology platform. c. Use CasesSee what's possible with SAP BTP. Learn how to identify business gaps and follow concrete implementation examples to understand how SAP BTP could fulfill your organization's specific needs. 1. Highlights include: 1) Application architecture 2) Administration 3) User interface 4) Application business logic 5) System and process integration 6) Data integration 7) Analytics 8) Security 9) Application development 10) Use cases

This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.

The cybersecurity of connected medical devices is one of the biggest challenges facing healthcare today. The compromise of a medical device can result in severe consequences for both patient health and patient data. Cybersecurity for Connected Medical Devices covers all aspects of medical device cybersecurity, with a focus on cybersecurity capability development and maintenance, system and software threat modeling, secure design of medical devices, vulnerability management, and integrating cybersecurity design aspects into a medical device manufacturer's Quality Management Systems (QMS). This book is geared towards engineers interested in the medical device cybersecurity space, regulatory, quality, and human resources specialists, and organizational leaders interested in building a medical device cybersecurity program.

Get your warehouses up and running in SAP S/4HANA! With this implementation guide to extended warehouse management (EWM) in SAP S/4HANA, lay the foundation by setting up your organizational and warehouse structures. Then configure your master data and cross-process settings with step-by-step instructions. Finally, customize your core processes, from inbound and outbound deliveries to value-added services and cartonization. Get the most out of SAP S/4HANA for your warehouses! Highlights include: 1) Master data 2) Warehouse structures 3) Goods receipt and issue 4) Putaway 5) Picking 6) Physical inventory 7) Monitoring 8) Shipping and receiving 9) Labor management 10) Value-added services (VAS) 11) Integration

Implement future-proof solutions for all types of teams with Data Center by learning about performance, reliability, scalability, and security Purchase of the print or Kindle book includes a free PDF Key Features Explore all of Jira's core features as well as the advanced features offered by Data Center Learn to use Jira for issue management, field management, screen management, and business workflows Install, update, and manage third-party apps from Atlassian marketplace to extend Jira capabilities Book DescriptionThis new and improved sixth edition comes with the latest Jira 8.21 Data Center offerings, with enhanced features such as clustering, advanced roadmaps, custom field optimization, and tools to track and manage tasks for your projects. This comprehensive guide to Jira 8.20.x LTS version provides updated content on project tracking, issue and field management, workflows, Jira Service Management, and security. The book begins by showing you how to plan and set up a new Jira instance from scratch before getting you acquainted with key features such as emails, workflows, and business processes. You'll also get to grips with Jira's data hierarchy and design and work with projects. Since Jira is used for issue management, this book will help you understand the different issues that can arise in your projects. As you advance, you'll create new screens from scratch and customize them to suit your requirements. Workflows, business processes, and guides on setting up incoming and outgoing mail servers will be covered alongside Jira's security model and Jira Service Management. Toward the end, you'll learn how Jira capabilities are extended with third-party apps from Atlassian marketplace. By the end of this Jira book, you'll have understood core components and functionalities of Jira and be able to implement them in business projects with ease. What you will learn Examine various deployment options and system requirements for hosting Jira Data Center Understand Jira's data hierarchy and learn how to design and work with projects in Jira Use Jira for agile software projects, business process management, customer service support, and more Explore field configuration schemes and find out how to apply them to projects Develop and design customized screens and apply them to different projects Create configurable reports on projects and share information through dashboards for reporting and analysis Who this book is forThis book is especially useful for project managers, but it's also intended for other Jira users, including developers, and any other industry besides software development, who would like to leverage Jira's powerful task management and workflow features to better manage their business processes.

The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice.

Enterprise developers face several challenges when it comes to building serverless applications, such as integrating applications and building container images from source. With more than 60 practical recipes, this cookbook helps you solve these issues with Knative--the first serverless platform natively designed for Kubernetes. Each recipe contains detailed examples and exercises, along with a discussion of how and why it works. If you have a good understanding of serverless computing and Kubernetes core resources such as deployment, services, routes, and replicas, the recipes in this cookbook show you how to apply Knative in real enterprise application development. Authors Kamesh Sampath and Burr Sutter include chapters on autoscaling, build and eventing, observability, Knative on OpenShift, and more. With this cookbook, you'll learn how to: Efficiently build, deploy, and manage modern serverless workloads Apply Knative in real enterprise scenarios, including advanced eventing Monitor your Knative serverless applications effectively Integrate Knative with CI/CD principles, such as using pipelines for faster, more successful production deployments Deploy a rich ecosystem of enterprise integration patterns and connectors in Apache Camel K as Kubernetes and Knative components

Statistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching experience. With a wealth of hands-on exercises and online resources created by the author, practice your skills using the data sets and R scripts from the book with detailed screencasts that accompany each script. This book is ideal for anyone looking to: * Complete an introductory course in statistics * Prepare for more advanced statistical courses * Gain the transferable analytical skills needed to interpret research from across the social sciences * Learn the technical skills needed to present data visually * Acquire a basic competence in the use of R and RStudio. This edition also includes a gentle introduction to Bayesian methods integrated throughout. The author has created a wide range of online resources, including: over 90 R scripts, 36 datasets, 37 screen casts, complete solutions for all exercises, and 130 multiple-choice questions to test your knowledge.

Starting from a basic knowledge of mathematics and mechanics gained in standard foundation classes, "Theory of Lift: Introductory Computational Aerodynamics in MATLAB/Octave" takes the reader conceptually through from the fundamental mechanics of lift to the stage of actually being able to make practical calculations and predictions of the coefficient of lift for realistic wing profile and planform geometries.

The classical framework and methods of aerodynamics are covered in detail and the reader is shown how they may be used to develop simple yet powerful MATLAB or Octave programs that accurately predict and visualise the dynamics of real wing shapes, using lumped vortex, panel, and vortex lattice methods.

This book contains all the mathematical development and formulae required in standard incompressible aerodynamics as well as dozens of small but complete working programs which can be put to use immediately using either the popular MATLAB or free Octave computional modelling packages.

Key features: Synthesizes the classical foundations of aerodynamics with hands-on computation, emphasizing interactivity and visualization.Includes complete source code for all programs, all listings having been tested for compatibility with both MATLAB and Octave.Companion website (www.wiley.com/go/mcbain) hosting codes and solutions.

"Theory of Lift: Introductory Computational Aerodynamics in MATLAB/Octave" is an introductory text for graduate and senior undergraduate students on aeronautical and aerospace engineering courses and also forms a valuable reference for engineers and designers.

- includes MATLABr fundamentals, matrices, arrays, general graphics and specialized plots in quality assurance problems, script files, ordinary and partial differential equations - gives calculation of six sigma, total quality management, time series forecasting, reliability, process improvement, metrology, quality control and assurance, measurement and testing techniques - provides tools for graphical presentation, basic and special statistics and testing, ordinary and partial differential solvers, and fitting tools - includes comprehensive command information in tables Many books are available on MATLABr programming for engineers in general or in some specific area, but none in the highly topical field of quality assurance (QA). MATLABr in quality assurance sciences fills this gap as a compact guide for students, engineers, and scientists in this field. It concentrates on MATLABr fundamentals with examples of application to a wide range of current problems from general, nano and bio-technology, and statistical control, to medicine and industrial management. Examples cover both the school and advanced level; comprising calculations of total quality management, six sigma, time series, process improvement, metrology, quality control, human factors in quality assurance, measurement and testing techniques, quality project and function management, and customer satisfaction. The book covers key topics, including: the basics of software with examples; graphics and representations; numerical computation, scripts and functions for QA calculations; ODE and PDEPE solvers applied to QA problems; curve fitting and time series tool interfaces in calculations of quality; and statistics calculations applied to quality testing.

30th European Symposium on Computer Aided Chemical Engineering, Volume 47 contains the papers presented at the 30th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Milan, Italy, May 24-27, 2020. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries.

Multi-Paradigm Modelling for Cyber-Physical Systems explores modeling and analysis as crucial activities in the development of Cyber-Physical Systems, which are inherently cross-disciplinary in nature and require distinct modeling techniques related to different disciplines, as well as a common background knowledge. This book will serve as a reference for anyone starting in the field of CPS who needs a solid foundation of modeling, including a comprehensive introduction to existing techniques and a clear explanation of their advantages and limitations. This book is aimed at both researchers and practitioners who are interested in various modeling paradigms across computer science and engineering.

Now in full color, this edition of Learning Tableau will empower you to bring data to life and make better business decisions Key Features * Learn the basics of data analysis, from snappy visualizations to comprehensive dashboards, now in full color * Gain meaningful insights with geospatial analysis, scripting extensions, and other advanced methods * Explore the latest Tableau 2022 features, including Einstein Discovery and Explain Data Book Description Learning Tableau 2022 helps you get started with Tableau and data visualization, but it does more than just cover the basic principles. It helps you understand how to analyze and communicate data visually, and articulate data stories using advanced features. This new edition is updated with Tableau's latest features, such as dashboard extensions, Explain Data, and integration with Einstein Discovery, which will help you harness the full potential of artificial intelligence (AI) and predictive modeling in Tableau. After an exploration of the core principles, this book will teach you how to use table and level of detail calculations to extend and alter default visualizations, build interactive dashboards, and master the art of telling stories with data. You'll learn about visual statistical analytics and create different types of static and animated visualizations and dashboards for rich user experiences. We then move on to interlinking different data sources with Tableau's Data Model capabilities, along with maps and geospatial visualization. You will further use Tableau Prep Builder's ability to efficiently clean and structure data. By the end of this book, you will be proficient in implementing the powerful features of Tableau 2022 to improve the business intelligence insights you can extract from your data. What you will learn * Develop stunning visualizations to explain complex data with clarity * Build interactive dashboards to drive actionable user insights for large datasets * Explore Data Model capabilities and interlink data from various sources * Create and use calculations to solve problems and enrich your data analytics * Enable smart decision-making with data clustering, distribution, and forecasting * Extend Tableau's native functionality with extensions, scripts, and Einstein Discovery AI * Leverage Tableau Prep Builder's amazing capabilities for data cleaning and structuring * Share your data stories to build a culture of trust and action Who This Book Is For This Tableau book is for aspiring BI developers and data analysts, data scientists, researchers, and anyone else who wants to gain a deeper understanding of data through Tableau. This book starts from the ground up, so you won't need any prior experience with Tableau before you dive in, but a full Tableau license (or 14-day demo license) is essential to be able to make use of all the exercises.

Dive into the new SAP C/4HANA suite. Understand how SAP C/4HANA handles marketing, commerce, sales, service, and customer data processes-and identify which solutions fit your organization's CX needs. Then explore integrations to SAP S/4HANA, extensions using SAP Cloud Platform, and applied artificial intelligence using SAP Leonardo. Learn how can serve your customers better-from the demand chain all the way down to the supply chain! Key Features: Get to know SAP C/4HANA, the new SAP Customer Experience suite. Explore marketing, commerce, sales, service, and customers.

"If mathematical modeling is the process of turning real phenomena into mathematical abstractions, then numerical computation is largely about the transformation from abstract mathematics to concrete reality. Many science and engineering disciplines have long benefited from the tremendous value of the correspondence between quantitative information and mathematical manipulation." -from the Preface Fundamentals of Numerical Computation is an advanced undergraduate-level introduction to the mathematics and use of algorithms for the fundamental problems of numerical computation: linear algebra, finding roots, approximating data and functions, and solving differential equations. The book is organized with simpler methods in the first half and more advanced methods in the second half, allowing use for either a single course or a sequence of two courses. The authors take readers from basic to advanced methods, illustrating them with over 200 self-contained MATLAB functions and examples designed for those with no prior MATLAB experience. Although the text provides many examples, exercises, and illustrations, the aim of the authors is not to provide a cookbook per se, but rather an exploration of the principles of cooking. Professors Driscoll and Braun have developed an online resource that includes well-tested materials related to every chapter. Among these materials are lecture-related slides and videos, ideas for student projects, laboratory exercises, computational examples and scripts, and all the functions presented in the book.

Cohesively Incorporates Statistical Theory with R Implementation Since the publication of the popular first edition of this comprehensive textbook, the contributed R packages on CRAN have increased from around 1,000 to over 6,000. Designed for an intermediate undergraduate course, Probability and Statistics with R, Second Edition explores how some of these new packages make analysis easier and more intuitive as well as create more visually pleasing graphs. New to the Second Edition Improvements to existing examples, problems, concepts, data, and functions New examples and exercises that use the most modern functions Coverage probability of a confidence interval and model validation Highlighted R code for calculations and graph creation Gets Students Up to Date on Practical Statistical Topics Keeping pace with today's statistical landscape, this textbook expands your students' knowledge of the practice of statistics. It effectively links statistical concepts with R procedures, empowering students to solve a vast array of real statistical problems with R. Web Resources A supplementary website offers solutions to odd exercises and templates for homework assignments while the data sets and R functions are available on CRAN.

The Feature-Driven Method for Structural Optimization details a novel structural optimization method within a CAD framework, integrating structural optimization and feature-based design. The book presents cutting-edge research on advanced structures and introduces the feature-driven structural optimization method by regarding engineering features as basic design primitives. Consequently, it presents a method that allows structural optimization and feature design to be done simultaneously so that feature attributes are preserved throughout the design process. The book illustrates and supports the effectiveness of the method described, showing potential applications through numerical modeling techniques and programming. This volume presents a high-performance optimization method adapted to engineering structures-a novel perspective that will help engineers in the computation, modeling and design of advanced structures.