Products related to Modern:
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Modern Data Visualization with R
Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights.It starts with basic graphs such as bar charts, scatter plots, and line charts, but progresses to less well-known visualizations such as tree maps, alluvial plots, radar charts, mosaic plots, effects plots, correlation plots, biplots, and the mapping of geographic data.Both static and interactive graphics are described and the use of color, shape, shading, grouping, annotation, and animations are covered in detail.The book moves from a default look and feel for graphs, to graphs with customized colors, fonts, legends, annotations, and organizational themes. FeaturesContains a wide breadth of graph types including newer and less well-known approachesConnects each graph type to the characteristics of the data and the goals of the analysisMoves the reader from simple graphs describing one variable to building visualizations that describe complex relationships among many variablesProvides newer approaches to creating interactive web graphics via JavaScript librariesDetails how to customize each graph type to meet users’ needs and those of their audiencesGives methods for creating visualizations that are publication ready for print (in color or black and white) and the webSuggests best practicesOffers examples from a wide variety of fieldsThe book is written for those new to data analysis as well as the seasoned data scientist.It can be used for both teaching and research, and will particularly appeal to anyone who needs to describe data visually and wants to find and emulate the most appropriate method quickly.The reader should have some basic coding experience, but expertise in R is not required.Some of the later chapters (e.g., visualizing statistical models) assume exposure to statistical inference at the level of analysis of variance and regression.
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Modern Business Analytics ISE
Written by Matt Taddy, successful author of the McGraw Hill Professional title, Business Data Science graduate of University of Chicago and Amazon Chief Economist.This new higher-ed text takes a practical, modern approach to data science and business analytics for the graduate-level business analytics student or professional.It takes a learn-by-doing approach, with real data analysis examples that explain the "why", rather than the "what" in the decision-making discussions.It uses R as the primary technology throughout the text and includes an end-of-chapter reference to the basic R recipes in each chapter. The text uses tools from economics and statistics in combination with Machine Learning Techniques to create a platform for using data to make decisions.The Connect product that supports the text includes Interactive Activities that have students explore content more deeply, Excel activities like Integrated Excel & Applying Excel, and a Prep Course that helps students refresh on fundamental pre-requisite knowledge they need to know prior to this course.
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Trading Territories : Mapping the Early Modern World
Trading Territories tells the compelling story of maps and geographical knowledge in the early modern world from the fifteenth to the early seventeenth century.Examining how European geographers mapped the territories of the Old World -Africa and Southeast Asia - this book shows how the historical preoccupation with Columbus's `discovery' of the New World of America in 1492 obscured the ongoing importance of mapping territories that have since been defined as `eastern', especially those in the Muslim world. In this book, now available in paperback and updated with a new preface by the author, Jerry Brotton shows that trade and diplomacy defined the development of maps and globes in this period, far more than the disinterested pursuit of scientific accuracy and objectivity, and challenges our preconceptions about not just maps, but also the history and geography of what we call East and West.
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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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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.
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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.
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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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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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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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Mapping Modern Theology - A Thematic and Historical Introduction
This textbook offers a fresh approach to modern theology by approaching the field thematically, covering classic topics in Christian theology over the last two hundred years.The editors, leading authorities on the history of nineteenth- and twentieth-century theology, have assembled a respected team of international scholars to offer substantive treatment of important doctrines and key debates in modern theology.Contributors include Kevin Vanhoozer, John Webster, Veli-Matti Kärkkäinen, and Michael Horton.The volume enables readers to trace how key doctrinal questions were discussed, where the main debates lie, and how ideas developed.Topics covered include the Trinity, divine attributes, creation, the atonement, ethics, practical theology, and ecclesiology.
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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 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 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.
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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.
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Is Lebanon modern?
Lebanon is considered a modern country in many aspects. It has a diverse and vibrant culture, a well-developed banking and financial sector, and a growing technology industry. However, it also faces challenges such as political instability, economic crises, and infrastructure issues. Overall, Lebanon can be considered modern in some areas, but it also struggles with modernization in others.
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Is Germany modern?
Yes, Germany is considered a modern country. It is known for its advanced technology, strong economy, efficient infrastructure, and high standard of living. Germany is also a leader in various industries such as automotive, engineering, and renewable energy. Additionally, the country has a well-developed healthcare and education system, further contributing to its modern status.
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