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  • Unreliable Narration and Trustworthiness : Intermedial and Interdisciplinary Perspectives
    Unreliable Narration and Trustworthiness : Intermedial and Interdisciplinary Perspectives

    Though the phenomenon known as “unreliable narration” or “narrative unreliability” has received a lot of attention during the last two decades, narratological research has mainly focused on its manifestations in narrative fiction, particularly in homodiegetic or first-person narration.Except for film, forms and functions of unreliable narration in other genres, media and disciplines have so far been relatively neglected.The present volume redresses the balance by directing scholarly attention to disciplines and domains that narratology has so far largely ignored.It aims at initiating an interdisciplinary approach to, and debate on, narrative unreliability, exploring unreliable narration in a broad range of literary genres, other media and non-fictional text-types, contexts and disciplines beyond literary studies.Crossing the boundaries between genres, media, and disciplines, the volume acknowledges that the question of whether or not to believe or trust a narrator transcends the field of literature: The issues of (un)reliability and (un)trustworthiness play a crucial role in many areas of human life as well as a wide spectrum of academic fields ranging from law to history, and from psychology to the study of culture.

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  • Data Governance: The Definitive Guide : People, Processes, and Tools to Operationalize Data Trustworthiness
    Data Governance: The Definitive Guide : People, Processes, and Tools to Operationalize Data Trustworthiness

    As you move data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure your organization meets compliance requirements.Data governance incorporates the ways people, processes, and technology work together to ensure data is trustworthy and can be used effectively.This practical guide shows you how to effectively implement and scale data governance throughout your organization. Chief information, data, and security officers and their teams will learn strategy and tooling to support democratizing data and unlocking its value while enforcing security, privacy, and other governance standards.Through good data governance, you can inspire customer trust, enable your organization to identify business efficiencies, generate more competitive offerings, and improve customer experience.This book shows you how. You'll learn:Data governance strategies addressing people, processes, and toolsBenefits and challenges of a cloud-based data governance approachHow data governance is conducted from ingest to preparation and useHow to handle the ongoing improvement of data qualityChallenges and techniques in governing streaming dataData protection for authentication, security, backup, and monitoringHow to build a data culture in your organization

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  • The Trustworthiness of God’s Words : Why the Reliability of Every Word from God Matters
    The Trustworthiness of God’s Words : Why the Reliability of Every Word from God Matters

    This is a book about God’s jealousy for his integrity, his passion to be believed, on the basis of his words alone.Throughout Scripture God expresses his determination to be known as the God who keeps his words.He has resolved that every person and nation will see and confess that all his words are reliable down to every last syllable, jot, and tittle.Learning to trust a God who is sovereign and in control, especially in the ache and throb of life, means hanging on to the conviction that everything he says is utterly dependable.  Knowing that God’s words are trustworthy and living it out can be two different things though, so as well as laying out the theological foundations, Layton MacDonald Talbert explores the practical applications.What does trusting God’s words look like in real life and how has it played out in the experience of God’s people?Let Talbert show you how in tracing the reliability of God through history we can learn to trust him with the future.

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  • Data Analytics & Visualization All-in-One For Dummies
    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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  • How can one verify the trustworthiness of providers?

    One way to verify the trustworthiness of providers is to check for reviews and ratings from other customers. Reading about other people's experiences can give you an idea of the quality of service provided. Additionally, you can look for any certifications or accreditations that the provider may have, as these can indicate a level of professionalism and adherence to industry standards. Finally, asking for references or recommendations from friends, family, or colleagues who have used the provider's services can also help in verifying their trustworthiness.

  • 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.

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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 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.

    Price: 105.00 £ | Shipping*: 0.00 £
  • 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.

    Price: 76.99 £ | Shipping*: 0.00 £
  • 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.

  • What is the function of spatial visualization ability?

    Spatial visualization ability allows individuals to mentally manipulate and understand spatial relationships between objects. This ability is crucial in fields such as engineering, architecture, and design, where individuals need to visualize and manipulate complex 3D objects and structures. It also plays a key role in tasks such as navigation, map reading, and understanding geometric concepts. Overall, spatial visualization ability is important for problem-solving, creativity, and understanding the physical world.

  • What does it mean if someone lacks spatial visualization skills?

    If someone lacks spatial visualization skills, it means that they have difficulty mentally manipulating and understanding spatial relationships between objects and shapes. This can manifest as challenges in tasks such as reading maps, understanding 3D objects, or visualizing how objects fit together in space. People with this difficulty may struggle with activities such as assembling furniture, reading graphs, or understanding geometric concepts. It's important to note that lacking spatial visualization skills does not indicate a lack of intelligence, but rather a specific cognitive challenge in this area.

  • Is there an app that can help improve and train one's spatial visualization skills?

    Yes, there are several apps available that can help improve and train spatial visualization skills. Apps like Lumosity, Peak, and Spatial IQ are designed to enhance spatial reasoning, mental rotation, and visualization abilities through various exercises and challenges. These apps offer a fun and interactive way to practice and develop spatial skills, which can be beneficial for tasks that require mental manipulation of objects in space, such as engineering, architecture, and mathematics.

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