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    Data Analytics & Visualization All-in-One For Dummies

    Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place.Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling.Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one.You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau.You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level.With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sourcesOrganize and analyze data Use data to tell a story with TableauExpand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data.Get ready to watch as your career in data takes off.

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  • Spatial Analysis with R : Statistics, Visualization, and Computational Methods
    Spatial Analysis with R : Statistics, Visualization, and Computational Methods

    In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R.The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis.Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data miningThis second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.

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  • Spatial Epidemiological Approaches in Disease Mapping and Analysis
    Spatial Epidemiological Approaches in Disease Mapping and Analysis

    Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries.Describing the wide range of available methods and key GIS concepts for spatial epidemiology, this book illustrates the utilities of the software using real-world data.Additional topics include geographic data models, address matching, geostatistical analysis, universal kriging, point pattern analysis, kernel density, spatio-temporal display, and disease surveillance.

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  • Crime Mapping and Spatial Data Analysis using R
    Crime Mapping and Spatial Data Analysis using R

    Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis.This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis.It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis.It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence.In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data.We then introduce a series of tools to study spatial homogeneity and dependence.A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation.The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space.In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.

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  • What is the inverse function of the preimage?

    The inverse function of the preimage is the function that maps the output of the preimage back to its original input. In other words, if the preimage function takes an input and maps it to a certain output, the inverse function will take that output and map it back to the original input. This allows us to "reverse" the mapping of the preimage function. The inverse function is denoted as f^(-1) and is used to undo the effects of the original preimage function.

  • What is the mathematical definition of a mapping and what are the terms image set and preimage set?

    A mapping, also known as a function, is a relation between two sets where each element in the first set is associated with exactly one element in the second set. Formally, a mapping from set A to set B is a rule or correspondence that assigns to each element a in set A exactly one element b in set B. The set A is called the domain of the mapping, and the set B is called the codomain. The image set of a mapping is the set of all elements in the codomain that are associated with at least one element in the domain. The preimage set of a mapping is the set of all elements in the domain that are associated with at least one element in the codomain.

  • How can I prove the statements about image and preimage?

    To prove statements about image and preimage, you can use the definitions and properties of these concepts. For the image of a set under a function, you can show that every element in the image set has a corresponding element in the original set. For the preimage of a set under a function, you can demonstrate that every element in the preimage set maps to an element in the target set. Additionally, you can use specific examples and counterexamples to illustrate the properties of image and preimage. Finally, you can also use mathematical reasoning and logic to prove the statements about image and preimage.

  • What is an identity function and what is a preimage?

    An identity function is a function that returns the same value that is input into it. In other words, the output is equal to the input. It is denoted as f(x) = x. A preimage is the original input value of a function before it undergoes a transformation. In other words, it is the value that gets mapped to a specific output value.

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  • An Introduction to R for Spatial Analysis and Mapping
    An Introduction to R for Spatial Analysis and Mapping

    The ever-expanding availability of spatial data continues to revolutionise research.This book is your go-to guide to getting the most out of handling, mapping and analysing location-based data. Without assuming prior knowledge of GIS, geocomputation or R, this book helps you understand spatial analysis and mapping and develop your programming skills, from learning about scripting and writing functions to point pattern analysis and spatial attribute analysis. The book:Illustrates approaches to analysis on a range of datasets that are new to this edition. Enables you to put your skills into practice with embedded exercises and over 30 self-test questions. Showcases the possibilities of using spatial analysis to explore spatial inequalities. Whether you’re an R novice or experienced user, this book equips upper undergraduates, postgraduates and researchers with the tools needed for spatial data handling and rich analysis.

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  • Advanced video mapping techniques - Spatial Augmented Reality applied to cultural heritage
    Advanced video mapping techniques - Spatial Augmented Reality applied to cultural heritage

    Spatial Augmented Reality applied to cultural heritage.

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  • Pro Power BI Desktop : Self-Service Analytics and Data Visualization for the Power User
    Pro Power BI Desktop : Self-Service Analytics and Data Visualization for the Power User

    Deliver eye-catching and insightful business intelligence with Microsoft Power BI Desktop.This new edition has been updated to cover all the latest features of Microsoft’s continually evolving visualization product.New in this edition is help with storytelling—adapted to PCs, tablets, and smartphones—and the building of a data narrative.You will find coverage of templates and JSON style sheets, data model annotations, and the use of composite data sources.Also provided is an introduction to incorporating Python visuals and the much awaited Decomposition Tree visual. Pro Power BI Desktop shows you how to use source data to produce stunning dashboards and compelling reports that you mold into a data narrative to seize your audience’s attention.Slice and dice the data with remarkable ease and then add metrics and KPIs to project the insights that create your competitive advantage.Convert raw data into clear, accurate, and interactive information with Microsoft’s free self-service BI tool. This book shows you how to choose from a wide range of built-in and third-party visualization types so that your message is always enhanced.You will be able to deliver those results on PCs, tablets, and smartphones, as well as share results via the cloud.The book helps you save time by preparing the underlying data correctly without needing an IT department to prepare it for you.What You Will LearnDeliver attention-grabbing information, turning data into insightFind new insights as you chop and tweak your data as never beforeBuild a data narrative through interactive reports with drill-through and cross-page slicingMash up data from multiple sources into a cleansed and coherent data modelBuild interdependent charts, maps, and tables to deliver visually stunninginformationCreate dashboards that help in monitoring key performance indicators of your businessAdapt delivery to mobile devices such as phones and tabletsWho This Book Is ForPower users who are ready to step up to the big leagues by going beyond what Microsoft Excel by itself can offer.The book also is for line-of-business managers who are starved for actionable data needed to make decisions about their business. And the book is for BI analysts looking for an easy-to-use tool to analyze data and share results with C-suite colleagues they support.

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  • Visualization, Visual Analytics and Virtual Reality in Medicine : State-of-the-art Techniques and Applications
    Visualization, Visual Analytics and Virtual Reality in Medicine : State-of-the-art Techniques and Applications

    Visualization, Visual Analytics and Virtual Reality in Medicine: State-of-the-art Techniques and Applications describes important techniques and applications that show an understanding of actual user needs as well as technological possibilities.The book includes user research, for example, task and requirement analysis, visualization design and algorithmic ideas without going into the details of implementation.This reference will be suitable for researchers and students in visualization and visual analytics in medicine and healthcare, medical image analysis scientists and biomedical engineers in general. Visualization and visual analytics have become prevalent in public health and clinical medicine, medical flow visualization, multimodal medical visualization and virtual reality in medical education and rehabilitation.Relevant applications now include digital pathology, virtual anatomy and computer-assisted radiation treatment planning.

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  • What is spatial visualization ability?

    Spatial visualization ability refers to the capacity to mentally manipulate and comprehend spatial relationships between objects. Individuals with strong spatial visualization skills can easily visualize and understand how objects relate to each other in space, such as rotating or manipulating shapes in their mind. This ability is crucial in various fields such as engineering, architecture, and mathematics, as it allows individuals to solve complex problems and understand spatial concepts more effectively. Improving spatial visualization ability can enhance problem-solving skills and overall cognitive performance.

  • Is spatial visualization important for engineers?

    Yes, spatial visualization is important for engineers as it allows them to mentally manipulate and understand complex 3D objects and structures. Engineers often need to design and analyze various components and systems, and spatial visualization skills help them to conceptualize and communicate their ideas effectively. Whether it's designing a new product, creating blueprints for a building, or solving complex problems, spatial visualization is a crucial skill that allows engineers to think critically and innovate in their field.

  • Can one improve their spatial visualization skills?

    Yes, it is possible to improve spatial visualization skills through practice and training. Engaging in activities such as puzzles, building models, and playing spatial reasoning games can help develop these skills. Additionally, practicing mental rotation exercises and regularly challenging oneself with spatial tasks can also contribute to improvement. With consistent effort and dedication, individuals can enhance their spatial visualization abilities over time.

  • What are problems with spatial visualization skills?

    Some problems with spatial visualization skills include difficulty in understanding and interpreting maps, graphs, and diagrams. Individuals with poor spatial visualization skills may struggle with tasks such as navigating through unfamiliar environments, understanding 3D objects, and mentally rotating objects. This can impact their performance in subjects such as math, science, and engineering, as well as in everyday activities such as driving and assembling furniture. Additionally, poor spatial visualization skills can lead to frustration and decreased confidence in one's abilities.

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