Meaningful Graphs

Meaningful Graphs

Author: James M. Smith

Publisher:

Published: 2014-06-01

Total Pages: 228

ISBN-13: 9780986054907

DOWNLOAD EBOOK

Meaningful Graphs is a concise and practical go-to guide for creating charts in Excel (r) that clearly and accurately tell the story in your data. It incorporates (a) explanations of the graph design principles of the experts (Tufte, Few, Robbins, Zelazny, and others), (b) the software steps necessary to incorporate these principles into Excel (r) charts, and (c) chart-related discussions of quality improvement (including Pareto charts), statistics (including run charts and correlations), and the use of graphs in PowerPoint (r) presentations (including chart animation). Also included are numerous "Tips" and "In Practice" examples drawn from over 35 years of working with data in healthcare settings. Coverage begins with highlighting the importance of knowing the story in your data and general principles of chart design (e.g., chartjunk, the use of color, consideration of three dimensional charts) and then proceeds to examine and create the five major chart types (column, bar, line, pie, scatter). This is followed by considerations of the pros and cons of each of the six less frequently employed chart types. There are over 120 graphs in full color plus tables and illustrations. Discussions of the most useful chart types include examples with accompanying data to facilitate practice. While illustrations are especially tailored for healthcare professionals (physicians, nurses, patient safety, quality improvement staff, executives, and managers) both in their work setting and in their academic preparation, the principles of graph design and the Excel (r) techniques required to incorporate these principles apply equally well in other settings. The latter include other industries and academic programs, including those leading to degrees in business administration (MBA), public health (MPH), and public administration (MPA). If you follow the advice in this book, the graphs you create for reports, presentations, posters, or publications will be more informative and more easily understo


Graphing Statistics & Data

Graphing Statistics & Data

Author: Anders Wallgren

Publisher: SAGE

Published: 1996-06-25

Total Pages: 100

ISBN-13: 9780761905998

DOWNLOAD EBOOK

This book introduces the technique and art of producing good charts. Carefully written with many examples and illustrations, the book begins with an introduction to the building blocks of charts (axes, scales and patterns) and then describes each step involved in creating effective and easy-to-read charts.


Storytelling with Data

Storytelling with Data

Author: Cole Nussbaumer Knaflic

Publisher: John Wiley & Sons

Published: 2015-10-09

Total Pages: 284

ISBN-13: 1119002265

DOWNLOAD EBOOK

Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!


Conceptual Graphs for Knowledge Representation

Conceptual Graphs for Knowledge Representation

Author: Guy W. Mineau

Publisher: Springer Science & Business Media

Published: 1993-07-14

Total Pages: 470

ISBN-13: 9783540569794

DOWNLOAD EBOOK

Artificial Intelligence and cognitive science are the two fields devoted to the study and development of knowledge-based systems (KBS). Over the past 25years, researchers have proposed several approaches for modeling knowledge in KBS, including several kinds of formalism such as semantic networks, frames, and logics. In the early 1980s, J.F. Sowa introduced the conceptual graph (CG) theory which provides a knowledge representation framework consisting of a form of logic with a graph notationand integrating several features from semantic net and frame representations. Since that time, several research teams over the world have been working on the application and extension of CG theory in various domains ranging from natural language processing to database modeling and machine learning. This volume contains selected papers fromthe international conference on Conceptual Structures held in the city of Quebec, Canada, August 4-7, 1993. The volume opens with invited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.


Graph Representation Learning

Graph Representation Learning

Author: William L. Hamilton

Publisher: Morgan & Claypool Publishers

Published: 2020-09-16

Total Pages: 161

ISBN-13: 168173964X

DOWNLOAD EBOOK

This book is a foundational guide to graph representation learning, including state-of-the art advances, and introduces the highly successful graph neural network (GNN) formalism. Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs -- a nascent but quickly growing subset of graph representation learning.


Show Me the Numbers

Show Me the Numbers

Author: Stephen Few

Publisher:

Published: 2012

Total Pages: 0

ISBN-13: 9780970601971

DOWNLOAD EBOOK

Information, no matter how important, cannot speak for itself. To tell its story, it relies on us to give it a clear voice. No information is more critical than quantitative data ... numbers that reveal what's happening, how our organizations are performing, and opportunities to do better. Numbers are usually presented in tables and graphs, but few are properly designed, resulting not only in poor communication, but at times in miscommunication. This is a travesty, because the skills needed to present quantitative information effectively are simple to learn. Good communication doesn't just happen; it is the result of good design.


Boost Graph Library

Boost Graph Library

Author: Jeremy G. Siek

Publisher: Pearson Education

Published: 2001-12-20

Total Pages: 464

ISBN-13: 0321601610

DOWNLOAD EBOOK

The Boost Graph Library (BGL) is the first C++ library to apply the principles of generic programming to the construction of the advanced data structures and algorithms used in graph computations. Problems in such diverse areas as Internet packet routing, molecular biology, scientific computing, and telephone network design can be solved by using graph theory. This book presents an in-depth description of the BGL and provides working examples designed to illustrate the application of BGL to these real-world problems. Written by the BGL developers, The Boost Graph Library: User Guide and Reference Manual gives you all the information you need to take advantage of this powerful new library. Part I is a complete user guide that begins by introducing graph concepts, terminology, and generic graph algorithms. This guide also takes the reader on a tour through the major features of the BGL; all motivated with example problems. Part II is a comprehensive reference manual that provides complete documentation of all BGL concepts, algorithms, and classes. Readers will find coverage of: Graph terminology and concepts Generic programming techniques in C++ Shortest-path algorithms for Internet routing Network planning problems using the minimum-spanning tree algorithms BGL algorithms with implicitly defined graphs BGL Interfaces to other graph libraries BGL concepts and algorithms BGL classes–graph, auxiliary, and adaptor Groundbreaking in its scope, this book offers the key to unlocking the power of the BGL for the C++ programmer looking to extend the reach of generic programming beyond the Standard Template Library.


Maps, Charts, Graphs & Diagrams

Maps, Charts, Graphs & Diagrams

Author: John Carratello

Publisher: Teacher Created Resources

Published: 1996-03

Total Pages: 82

ISBN-13: 1557341699

DOWNLOAD EBOOK

With this book, teachers can give students many hands-on opportunities to practice using these visual tools in a meaningful context. Students will learn how to read different types of maps, charts, graphs, and diagrams, as well as how to construct their own. They will learn which visual tools are best for presenting specific types of information.--Page 3.


Interpreting Graphs and Tables

Interpreting Graphs and Tables

Author: Peter H. Selby

Publisher: John Wiley & Sons

Published: 1976

Total Pages: 232

ISBN-13:

DOWNLOAD EBOOK

"Now you can teach yourself how to interpret the major types of graphs and tables and extract the most useful information from them. You'll find out how to handle and arrange raw data, tabulate and analyze data, and develop graphic formats for data presentation. And you'll learn how to recognize trends and relationships among data, read values form a wide variety of standard and special types of charts, and derive conclusions on the significance of data patterns. You need no special math background to have success with this guide."--Back cover.