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Spring Security
by Mick KnutsonSpring Security 4.2" is an incremental guide that will teach you how to protect your application from malicious users. Through this book, you will learn how to cleanly integrate Spring Security into your application using the latest technologies and frameworks with the help of detailed examples.
Springer Handbook of Global Navigation Satellite Systems (Springer Handbooks)
by Peter Teunissen Oliver MontenbruckThis Handbook presents a complete and rigorous overview of the fundamentals, methods and applications of the multidisciplinary field of Global Navigation Satellite Systems (GNSS), providing an exhaustive, one-stop reference work and a state-of-the-art description of GNSS as a key technology for science and society at large. All global and regional satellite navigation systems, both those currently in operation and those under development (GPS, GLONASS, Galileo, BeiDou, QZSS, IRNSS/NAVIC, SBAS), are examined in detail. The functional principles of receivers and antennas, as well as the advanced algorithms and models for GNSS parameter estimation, are rigorously discussed. The book covers the broad and diverse range of land, marine, air and space applications, from everyday GNSS to high-precision scientific applications and provides detailed descriptions of the most widely used GNSS format standards, covering receiver formats as well as IGS product and meta-data formats. The full coverage of the field of GNSS is presented in seven parts, from its fundamentals, through the treatment of global and regional navigation satellite systems, of receivers and antennas, and of algorithms and models, up to the broad and diverse range of applications in the areas of positioning and navigation, surveying, geodesy and geodynamics, and remote sensing and timing. Each chapter is written by international experts and amply illustrated with figures and photographs, making the book an invaluable resource for scientists, engineers, students and institutions alike.
Springer Handbook of Model-Based Science (Springer Handbooks)
by Lorenzo Magnani Tommaso BertolottiThis handbook offers the first comprehensive reference guide to the interdisciplinary field of model-based reasoning. It highlights the role of models as mediators between theory and experimentation, and as educational devices, as well as their relevance in testing hypotheses and explanatory functions. The Springer Handbook merges philosophical, cognitive and epistemological perspectives on models with the more practical needs related to the application of this tool across various disciplines and practices. The result is a unique, reliable source of information that guides readers toward an understanding of different aspects of model-based science, such as the theoretical and cognitive nature of models, as well as their practical and logical aspects. The inferential role of models in hypothetical reasoning, abduction and creativity once they are constructed, adopted, and manipulated for different scientific and technological purposes is also discussed. Written by a group of internationally renowned experts in philosophy, the history of science, general epistemology, mathematics, cognitive and computer science, physics and life sciences, as well as engineering, architecture, and economics, this Handbook uses numerous diagrams, schemes and other visual representations to promote a better understanding of the concepts. This also makes it highly accessible to an audience of scholars and students with different scientific backgrounds. All in all, the Springer Handbook of Model-Based Science represents the definitive application-oriented reference guide to the interdisciplinary field of model-based reasoning.
SPSS 24 für Dummies (Für Dummies)
by Felix BrosiusOb Kundendaten oder Absatzzahlen, Umfrageergebnisse oder wissenschaftliche Studien - große Datenmengen lassen sich am besten mit SPSS untersuchen, dem am häufigsten eingesetzten Softwaretool zur statistischen Datenanalyse. Mit "SPSS 24 für Dummies" erhalten Sie eine unterhaltsam geschriebene und zugleich sehr fundierte Einführung in dieses mächtige Programm. Werten Sie Daten professionell aus, kommen Sie auf dieser Basis zu belastbaren Ergebnissen, die Grundlage für Ihre Entscheidungen sein können, und machen Sie so umfangreiche Datenmengen zu wichtigen Informationsquellen.
SPSS Statistics for Data Analysis and Visualization
by Keith McCormick Jesus SalcedoDive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.
SPSS Statistics for Data Analysis and Visualization
by Keith McCormick Jesus SalcedoDive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.
SQL für Dummies (Für Dummies)
by Allen G. TaylorDaten und Datenbanken sind quasi überall. Mit der Standardabfragesprache SQL können Daten in relationalen Datenbanken einfach, strukturiert und zielsicher abgefragt werden. Erfahren Sie in diesem Buch, welches kein Vorwissen voraussetzt, wie man Datenbanken erstellt, wie man Daten ordnet und abfragt und wie man SQL-Anweisungen in Programme und Websites einbindet. Nutzen Sie dieses Buch auch als Nachschlagewerk. Ganz wichtig: Sie lernen auch, wie Sie Ihre Datenbanken und Daten schützen und wie Sie typische Fehler vermeiden.
SQL Server 2016 Developer's Guide
by Dejan Sarka Milos Radivojevic William DurkinGet the most out of the rich development capabilities of SQL Server 2016 to build efficient database applications for your organization About This Book • Utilize the new enhancements in Transact-SQL and security features in SQL Server 2016 to build efficient database applications • Work with temporal tables to get information about data stored in the table at any point in time • A detailed guide to SQL Server 2016, introducing you to multiple new features and enhancements to improve your overall development experience Who This Book Is For This book is for database developers and solution architects who plan to use the new SQL Server 2016 features for developing efficient database applications. It is also ideal for experienced SQL Server developers who want to switch to SQL Server 2016 for its rich development capabilities. Some understanding of the basic database concepts and Transact-SQL language is assumed. What You Will Learn • Explore the new development features introduced in SQL Server 2016 • Identify opportunities for In-Memory OLTP technology, significantly enhanced in SQL Server 2016 • Use columnstore indexes to get significant storage and performance improvements • Extend database design solutions using temporal tables • Exchange JSON data between applications and SQL Server in a more efficient way • Migrate historical data transparently and securely to Microsoft Azure by using Stretch Database • Use the new security features to encrypt or to have more granular control over access to rows in a table • Simplify performance troubleshooting with Query Store • Discover the potential of R's integration with SQL Server In Detail Microsoft SQL Server 2016 is considered the biggest leap in the data platform history of the Microsoft, in the ongoing era of Big Data and data science. Compared to its predecessors, SQL Server 2016 offers developers a unique opportunity to leverage the advanced features and build applications that are robust, scalable, and easy to administer. This book introduces you to new features of SQL Server 2016 which will open a completely new set of possibilities for you as a developer. It prepares you for the more advanced topics by starting with a quick introduction to SQL Server 2016's new features and a recapitulation of the possibilities you may have already explored with previous versions of SQL Server. The next part introduces you to small delights in the Transact-SQL language and then switches to a completely new technology inside SQL Server - JSON support. We also take a look at the Stretch database, security enhancements, and temporal tables. The last chapters concentrate on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. You will finally be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. By the end of this book, you will have the required information to design efficient, high-performance database applications without any hassle. Style and approach This book is a detailed guide to mastering the development features offered by SQL Server 2016, with a unique learn-as-you-do approach. All the concepts are explained in a very easy-to-understand manner and are supplemented with examples to ensure that you—the developer—are able to take that next step in building more powerful, robust applications for your organization with ease.
SQL Server 2017 Administrator's Guide
by Marek ChmelThis book will give you all the information you need to become an expert database administrator, and master the administrative aspects of SQL Server 2017. From setting up and configuring your SQL Server instance to fine-tuning your database by using various techniques, this extensive guide will teach you the nitty-gritty of SQL Server 2017 administration
SQL Server 2017 Integration Services Cookbook
by Dejan Sarka Christian Cote Matija LahHarness the power of SQL Server 2017 Integration Services to build your data integration solutions with ease About This Book • Acquaint yourself with all the newly introduced features in SQL Server 2017 Integration Services • Program and extend your packages to enhance their functionality • This detailed, step-by-step guide covers everything you need to develop efficient data integration and data transformation solutions for your organization Who This Book Is For This book is ideal for software engineers, DW/ETL architects, and ETL developers who need to create a new, or enhance an existing, ETL implementation with SQL Server 2017 Integration Services. This book would also be good for individuals who develop ETL solutions that use SSIS and are keen to learn the new features and capabilities in SSIS 2017. What You Will Learn • Understand the key components of an ETL solution using SQL Server 2016-2017 Integration Services • Design the architecture of a modern ETL solution • Have a good knowledge of the new capabilities and features added to Integration Services • Implement ETL solutions using Integration Services for both on-premises and Azure data • Improve the performance and scalability of an ETL solution • Enhance the ETL solution using a custom framework • Be able to work on the ETL solution with many other developers and have common design paradigms or techniques • Effectively use scripting to solve complex data issues In Detail SQL Server Integration Services is a tool that facilitates data extraction, consolidation, and loading options (ETL), SQL Server coding enhancements, data warehousing, and customizations. With the help of the recipes in this book, you'll gain complete hands-on experience of SSIS 2017 as well as the 2016 new features, design and development improvements including SCD, Tuning, and Customizations. At the start, you'll learn to install and set up SSIS as well other SQL Server resources to make optimal use of this Business Intelligence tools. We'll begin by taking you through the new features in SSIS 2016/2017 and implementing the necessary features to get a modern scalable ETL solution that fits the modern data warehouse. Through the course of chapters, you will learn how to design and build SSIS data warehouses packages using SQL Server Data Tools. Additionally, you'll learn to develop SSIS packages designed to maintain a data warehouse using the Data Flow and other control flow tasks. You'll also be demonstrated many recipes on cleansing data and how to get the end result after applying different transformations. Some real-world scenarios that you might face are also covered and how to handle various issues that you might face when designing your packages. At the end of this book, you'll get to know all the key concepts to perform data integration and transformation. You'll have explored on-premises Big Data integration processes to create a classic data warehouse, and will know how to extend the toolbox with custom tasks and transforms. Style and approach This cookbook follows a problem-solution approach and tackles all kinds of data integration scenarios by using the capabilities of SQL Server 2016 Integration Services. This book is well supplemented with screenshots, tips, and tricks. Each recipe focuses on a particular task and is written in a very easy-to-follow manner.
SQL Server on Linux
by Jasmin AzemovicBring the performance and security of SQL Server to Linux About This Book • Design and administer your SQL Server solution on the open source Linux platform • Install, configure, and fine-tune your database application for maximum performance • An easy-to-follow guide teaching you how to implement various SQL Server CTP 2.x offerings on Linux—from installation to administration Who This Book Is For This book is for the Linux users who want to learn SQL Server on their favorite Linux distributions. It is not important if you are experienced database user or a beginner as we are starting from scratch. However, it is recommended that you have basic knowledge about relational models. More advanced readers can pick the chapters of their interest and study specific topics immediately. Users from Windows platform can also benefit from this book to expand their frontiers and become equally efficient on both platforms. What You Will Learn • Install and set up SQL Server CTP 2.x on Linux • Create and work with database objects using SQL Server on Linux • Configure and administer SQL Server on Linux-based systems • Create and restore database back-ups • Protect sensitive data using the built-in cryptographic features • Optimize query execution using indexes • Improve query execution time by more than 10x using in-memory OLTP • Track row-versioning using temporal tables In Detail Microsoft's launch of SQL Server on Linux has made SQL Server a truly versatile platform across different operating systems and data-types, both on-premise and on-cloud. This book is your handy guide to setting up and implementing your SQL Server solution on the open source Linux platform. You will start by understanding how SQL Server can be installed on supported and unsupported Linux distributions. Then you will brush up your SQL Server skills by creating and querying database objects and implementing basic administration tasks to support business continuity, including security and performance optimization. This book will also take you beyond the basics and highlight some advanced topics such as in-memory OLTP and temporal tables. By the end of this book, you will be able to recognize and utilize the full potential of setting up an efficient SQL Server database solution in your Linux environment. Style and approach This book follows a step-by-step approach to teach readers the concepts of SQL Server on Linux using the bash command line and SQL programming language trough examples which can easily be adapted and applied in your own solutions.
Stabilization, Safety, and Security of Distributed Systems: 19th International Symposium, SSS 2017, Boston, MA, USA, November 5–8, 2017, Proceedings (Lecture Notes in Computer Science #10616)
by Paul Spirakis Philippas TsigasThis book constitutes the refereed proceedings of the 19th International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2017, held in Boston, MA, USA, in November 2017.The 29 revised full papers presented together with 8 revised short papers were carefully reviewed and selected from 68 initial submissions. This year the Symposium was organized into three tracks reflecting major trends related to self-* systems: Stabilizing Systems: Theory and Practice: Distributed Computing and Communication Networks; and Computer Security and Information Privacy.
Stable Analysis Patterns for Systems
by Mohamed FayadSoftware analysis patterns play an important role in reducing the overall cost and compressing the time of software project lifecycles. However, building reusable and stable software analysis patterns is still considered a major and delicate challenge. This book proposes a novel concept for building analysis patterns based on software stability and is a modern approach for building stable, highly reusable, and widely applicable analysis patterns. The book also aims to promote better understanding of problem spaces and discusses how to focus requirements analysis accurately. It demonstrates a new approach to discovering and creating stable analysis patterns (SAPs). This book presents a pragmatic approach to understanding problem domains, utilizing SAPs for any field of knowledge, and modeling stable software systems, components, and frameworks. It helps readers attain the basic knowledge that is needed to analyze and extract analysis patterns from any domain of interest. Readers also learn to master methods to document patterns in an effective, easy, and comprehensible manner. Bringing significant contributions to the field of computing, this book is a unique and comprehensive reference manual on SAPs. It provides insight on handling the understanding of problem spaces and supplies methods and processes to analyze user requirements accurately as well as ways to use SAPs in building myriad cost-effective and highly maintainable systems. The book also shows how to link SAPs to the design phase thereby ensuring a smooth transition between analysis and design.
Stable Analysis Patterns for Systems
by Mohamed FayadSoftware analysis patterns play an important role in reducing the overall cost and compressing the time of software project lifecycles. However, building reusable and stable software analysis patterns is still considered a major and delicate challenge. This book proposes a novel concept for building analysis patterns based on software stability and is a modern approach for building stable, highly reusable, and widely applicable analysis patterns. The book also aims to promote better understanding of problem spaces and discusses how to focus requirements analysis accurately. It demonstrates a new approach to discovering and creating stable analysis patterns (SAPs). This book presents a pragmatic approach to understanding problem domains, utilizing SAPs for any field of knowledge, and modeling stable software systems, components, and frameworks. It helps readers attain the basic knowledge that is needed to analyze and extract analysis patterns from any domain of interest. Readers also learn to master methods to document patterns in an effective, easy, and comprehensible manner. Bringing significant contributions to the field of computing, this book is a unique and comprehensive reference manual on SAPs. It provides insight on handling the understanding of problem spaces and supplies methods and processes to analyze user requirements accurately as well as ways to use SAPs in building myriad cost-effective and highly maintainable systems. The book also shows how to link SAPs to the design phase thereby ensuring a smooth transition between analysis and design.
Starting an Etsy Business For Dummies
by Kate Shoup Kate GatskiTurn your hobby into revenue with an expertly-run Etsy shop Starting an Etsy Business For Dummies is the all-in-one resource for building your own successful business. Arts and crafts are currently a $32 billion market in the U.S., and Etsy is the number-one way to grab a piece of it for yourself. Sales through the site are rising, fueled by Pinterest, Instagram, and other social media—so there's never been a better time to jump into the fray. This book shows you everything you need to know to get set up, get things running, and build your business as you see fit. From photography and sales writing, through SEO, homepage navigation, and more, you'll find it all here. This new third edition has been updated to cover Etsy's newest seller tools, including Pattern, Etsy Manufacturing, Etsy Shop Updates, and the Dashboard, with expert guidance on QuickBooks Self-Employed to help you keep your business's finances under control. With helpful information, tips, tools, and tricks, this book is your ultimate guide to building your own Etsy shop. Showcase your products to their best advantage with great photographs and compelling listings Learn the technical side of setting up shop and processing orders Manage your storefront efficiently using the latest Etsy tools and features Increase sales by connecting with other vendors and promoting on Pinterest Are you an artist, crafter, artisan, or craftsman? Etsy can be another great revenue stream. Are you just curious about whether your projects would sell? Wade in gradually to test the waters. Etsy is home to businesses of many sizes and types, and Starting an Etsy Business For Dummies shows you how to stake your claim.
Starting an Etsy Business For Dummies
by Kate Shoup Kate GatskiTurn your hobby into revenue with an expertly-run Etsy shop Starting an Etsy Business For Dummies is the all-in-one resource for building your own successful business. Arts and crafts are currently a $32 billion market in the U.S., and Etsy is the number-one way to grab a piece of it for yourself. Sales through the site are rising, fueled by Pinterest, Instagram, and other social media—so there's never been a better time to jump into the fray. This book shows you everything you need to know to get set up, get things running, and build your business as you see fit. From photography and sales writing, through SEO, homepage navigation, and more, you'll find it all here. This new third edition has been updated to cover Etsy's newest seller tools, including Pattern, Etsy Manufacturing, Etsy Shop Updates, and the Dashboard, with expert guidance on QuickBooks Self-Employed to help you keep your business's finances under control. With helpful information, tips, tools, and tricks, this book is your ultimate guide to building your own Etsy shop. Showcase your products to their best advantage with great photographs and compelling listings Learn the technical side of setting up shop and processing orders Manage your storefront efficiently using the latest Etsy tools and features Increase sales by connecting with other vendors and promoting on Pinterest Are you an artist, crafter, artisan, or craftsman? Etsy can be another great revenue stream. Are you just curious about whether your projects would sell? Wade in gradually to test the waters. Etsy is home to businesses of many sizes and types, and Starting an Etsy Business For Dummies shows you how to stake your claim.
State of the Art in Digital Media and Applications (SpringerBriefs in Computer Science)
by Rae EarnshawThis book presents the user-facing aspects of digital media, from the web and computer games, to mobile technologies and social media, and demonstrates how these are continuously growing and developing. The convergence of IT, telecommunications, and media is bringing about a revolution in the way information is collected, stored, accessed and distributed. Rae Earnshaw's book explores the principal factors driving this and the ways in which social and cultural contexts are affected by media content. This is Professor Earnshaw's fourth book in a series that focuses on digital media and creativity, and through the use of Case Studies; the theoretical, practical and technical aspects of digital media are examined. Readers are informed about how the user as content creator, publisher and broadcaster is changing the traditional roles of news media, publishers and entertainment corporations. Topics such as the evolution of digital imaging and the phenomenon of social media are discussed in relation to this. Professor Earnshaw also demonstrates how changes in technology produce shifts in the ways that consumers utilize it, in an increasing variety of application domains such as e-books, digital cameras, Facebook and Twitter.State of the Art in Digital Media and Applications will be invaluable for readers that want a comprehensive look at how emerging digital media technologies are being used, and how they are transforming how we create, consume, exchange and manipulate media content.
State-Space Approaches for Modelling and Control in Financial Engineering: Systems theory and machine learning methods (Intelligent Systems Reference Library #125)
by Gerasimos G. RigatosThe book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential equations (e.g. the Black–Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making.The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established.Covering the following key areas of financial engineering: (i) control and stabilization of financial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in financial engineering. It is also a useful resource for the engineering and computer science community
Static Analysis: 24th International Symposium, SAS 2017, New York, NY, USA, August 30 – September 1, 2017, Proceedings (Lecture Notes in Computer Science #10422)
by Francesco RanzatoThis book constitutes the refereed proceedings of the 24th International Static Analysis Symposium, SAS 2017, held in New York, NY, USA, in August/September 2017. The 22 papers presented in this volume were carefully reviewed and selected from 50 submissions. The papers cover various aspects of the presentation of theoretical, practical, and applicational advances in area of static analysis that is recognized as a fundamental tool for program verification, bug detection, compiler organization, program understanding, and software maintenance.
Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry (Frontiers in Probability and the Statistical Sciences)
by Susmita Datta Bart J. MertensThis book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies.Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass spectrometry, time-of-flight data, and Fourier transform mass spectrometry are but a selection of the measurement platforms available to the modern analyst. Thus in practical proteomics or metabolomics, researchers will not only be confronted with new high dimensional data types—as opposed to the familiar data structures in more classical genomics—but also with great variation between distinct types of mass spectral measurements derived from different platforms, which may complicate analyses, comparison, and interpretation of results.
Statistical Analysis with R For Dummies
by Joseph SchmullerUnderstanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results. Gets you up to speed on the #1 analytics/data science software tool Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling Shows you how R offers intel from leading researchers in data science, free of charge Provides information on using R Studio to work with R Get ready to use R to crunch and analyze your data—the fast and easy way!
Statistical Analysis with R For Dummies
by Joseph SchmullerUnderstanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results. Gets you up to speed on the #1 analytics/data science software tool Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling Shows you how R offers intel from leading researchers in data science, free of charge Provides information on using R Studio to work with R Get ready to use R to crunch and analyze your data—the fast and easy way!
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition
by Bruce RatnerInterest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. What is new in the Third Edition: The current chapters have been completely rewritten. The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition
by Bruce RatnerInterest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. What is new in the Third Edition: The current chapters have been completely rewritten. The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.
Statistical Application Development with R and Python - Second Edition
by Prabhanjan Narayanachar TattarSoftware Implementation Illustrated with R and Python About This Book • Learn the nature of data through software which takes the preliminary concepts right away using R and Python. • Understand data modeling and visualization to perform efficient statistical analysis with this guide. • Get well versed with techniques such as regression, clustering, classification, support vector machines and much more to learn the fundamentals of modern statistics. Who This Book Is For If you want to have a brief understanding of the nature of data and perform advanced statistical analysis using both R and Python, then this book is what you need. No prior knowledge is required. Aspiring data scientist, R users trying to learn Python and vice versa What You Will Learn • Learn the nature of data through software with preliminary concepts right away in R • Read data from various sources and export the R output to other software • Perform effective data visualization with the nature of variables and rich alternative options • Do exploratory data analysis for useful first sight understanding building up to the right attitude towards effective inference • Learn statistical inference through simulation combining the classical inference and modern computational power • Delve deep into regression models such as linear and logistic for continuous and discrete regressands for forming the fundamentals of modern statistics • Introduce yourself to CART – a machine learning tool which is very useful when the data has an intrinsic nonlinearity In Detail Statistical Analysis involves collecting and examining data to describe the nature of data that needs to be analyzed. It helps you explore the relation of data and build models to make better decisions. This book explores statistical concepts along with R and Python, which are well integrated from the word go. Almost every concept has an R code going with it which exemplifies the strength of R and applications. The R code and programs have been further strengthened with equivalent Python programs. Thus, you will first understand the data characteristics, descriptive statistics and the exploratory attitude, which will give you firm footing of data analysis. Statistical inference will complete the technical footing of statistical methods. Regression, linear, logistic modeling, and CART, builds the essential toolkit. This will help you complete complex problems in the real world. You will begin with a brief understanding of the nature of data and end with modern and advanced statistical models like CART. Every step is taken with DATA and R code, and further enhanced by Python. The data analysis journey begins with exploratory analysis, which is more than simple, descriptive, data summaries. You will then apply linear regression modeling, and end with logistic regression, CART, and spatial statistics. By the end of this book you will be able to apply your statistical learning in major domains at work or in your projects. Style and approach Developing better and smarter ways to analyze data. Making better decisions/future predictions. Learn how to explore, visualize and perform statistical analysis. Better and efficient statistical and computational methods. Perform practical examples to master your learning