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001453764 001__ 1453764
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001453764 019__ $$a1356891187
001453764 020__ $$a9781484286098$$q(electronic bk.)
001453764 020__ $$a148428609X$$q(electronic bk.)
001453764 020__ $$z1484286081
001453764 020__ $$z9781484286081
001453764 0247_ $$a10.1007/978-1-4842-8609-8$$2doi
001453764 035__ $$aSP(OCoLC)1357014889
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001453764 049__ $$aISEA
001453764 050_4 $$aQA276.4
001453764 08204 $$a005.55$$223/eng/20230110
001453764 1001_ $$aBessler, LeRoy.
001453764 24510 $$aVisual Data Insights Using SAS ODS Graphics :$$ba Guide to Communication-Effective Data Visualization /$$cLeRoy Bessler.
001453764 260__ $$aBerkeley, CA :$$bApress L.P.,$$c2023.
001453764 300__ $$a1 online resource (xix, 621 pages) :$$billustrations (chiefly color)
001453764 336__ $$atext$$btxt$$2rdacontent
001453764 337__ $$acomputer$$bc$$2rdamedia
001453764 338__ $$aonline resource$$bcr$$2rdacarrier
001453764 5058_ $$aIntro -- Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Part I: Design Principles -- Chapter 1: Principles of Communication-Effective Graphic Design -- Be Brief, Clear, Picturesque, and Accurate -- 3D Pie Charts Are Always Misleading -- 3D Bar Charts Are Anticommunicative -- Graphs Need Image and Precise Numbers -- A Usable Stacked Bar Chart Requires an Axis Table to Deliver the Precise Values -- A Clustered Horizontal Bar Chart Is Better Than a Stacked Bar Chart -- For Bar Charts, Horizontal Is Usually Better
001453764 5058_ $$aFor a Line Plot with Discrete X Values, an X Axis Table Is an Alternative to Annotation -- Curve Labels Eliminate the Need for a Legend -- Show Them What's Important -- Show Them What's Important with Ranking -- Show Them What's Important with Subsetting -- Three Ways to Do Ranked Subsetting -- Simplicity Accelerates and Facilitates Visual Insights into Data -- A Sparse Graph Is Easily and Quickly Interpreted -- Inform the Viewer About the Key Data Points of a Multi-line Overlay Plot -- For a Trend, Usually Start the Y Axis at Zero
001453764 5058_ $$aFor a Bar Chart, Unless There Are Negative Values, Always Start the Value Axis at Zero -- Use Maximally Simple Design to Focus on What's Important -- Tell Them What's Important with a Headline -- A Graph Footnote Does Not Need to Be Small -- Assure Text Readability -- Font Size and Font Weight Affect Readability -- Keep Text Horizontal -- Never Use Backgrounds-They Impair Readability -- Readability Depends on Display Situation -- A Graph Can Have a Companion Table -- Web Graphs -- Include Data Tips (a.k.a. Mouseover Text) -- A Web Graph Can Have a Companion Hyperlinked Excel Table
001453764 5058_ $$aA Web Graph Should Not Require Scrolling -- Summary -- Chapter 2: Principles of Communication-Effective Use of Color -- Avoid Red and Green for "Bad Versus Good" -- Color-Coding Data with a Multiple Shades of the Same Hue -- Use Color to Communicate, Not to Decorate -- Use of Color Can Confuse -- Establish and Use a Personal Color Palette for Consistency -- Beware of Color Names -- Benefits of Boring Black and White -- Color Requires Sufficient Mass to Be Distinguishable -- Never Use Background Images or Textured or Color Gradient Backgrounds -- Use a Plain Solid Color Background
001453764 5058_ $$aProvide High Contrast Between Text Color and Background Color -- Pie Charts and Color -- Emphasis Options for Colorless Text -- Choosing the Right Colors -- A Light Color Can Be the Right Color -- Uncolor Might Be the Right Color -- "Transparent" Color As the Right Color -- Color Differs on Different Media -- Color Systems -- RGB Colors -- HLS Colors -- Examples of Good Color Use -- Summary -- Part II: Widely Applicable Examples You Can Use -- Chapter 3: Introduction to SAS ODS Graphics -- Outer Structure of ODS Graphics Code in Examples -- Inner Structure of ODS Graphics Code -- Text Attributes Control in ODS Graphics
001453764 506__ $$aAccess limited to authorized users.
001453764 520__ $$aSAS ODS graphics users will learn in this book how to visually understand and communicate the significance of data to deliver images for quick and easy insight, with precise numbers. Many charts or plots require the viewer to run the eye from a bar end or plot point to some point on an axis, and then to interpolate between tick marks to estimate the value. Some design choices can lead to wrong conclusions or mistaken impressions. Graphic software relies on defaults to deliver something if you make a minimal effort, but that something is not likely to be exactly what you want. Visual Data Insights Using SAS ODS Graphics provides examples using experience-based design principles. It presents examples of bar charts, pie charts, and trend lines or time series plots, the graph types commonly used in business, other organizations, and the media for visual insight into data. Newer graphs are also included: dot plots, needle plots, waterfall charts, butterfly charts, heat maps, bubble plots, step plots, high-low plots, and donut charts. In addition, there are basic tools of statistics: scatter plots, box plots, histograms, fit and confidence plots, and distributions. Author LeRoy Bessler introduces unique creations, including sparsely annotated time series, maximally informative bar charts, better box plots, histograms based on interesting atypical rationales, and much more. The examples use SAS sample data sets as input. Any SAS user can experiment with the code presented to see what else is possible, or adapt it to repurpose the design and apply it with a customized version of that code. What You'll Learn Create graphs that are easily and quickly interpreted, and without ambiguity Supply precise data values that are correct on the graph and correctly associated with the graphic visual elements Take advantage of widely applicable (but not necessarily available elsewhere) design examples Avoid bad practices that are encouraged by poor examples elsewhere Get past sub-optimal designs and results that are built into software defaults Take advantage of less familiar capabilities available in the software Who This Book Is For SAS software users who want to understand their data and/or visually deliver their results.
001453764 588__ $$aDescription based on print version record.
001453764 63000 $$aSAS (Computer file)
001453764 650_0 $$aInformation visualization.
001453764 650_0 $$aComputer graphics.
001453764 655_0 $$aElectronic books.
001453764 77608 $$iPrint version:$$aBessler, LeRoy.$$tVisual Data Insights Using SAS ODS Graphics.$$dBerkeley, CA : Apress L.P., ©2023$$z9781484286081
001453764 852__ $$bebk
001453764 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-1-4842-8609-8$$zOnline Access$$91397441.1
001453764 909CO $$ooai:library.usi.edu:1453764$$pGLOBAL_SET
001453764 980__ $$aBIB
001453764 980__ $$aEBOOK
001453764 982__ $$aEbook
001453764 983__ $$aOnline
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