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References: Data Visualization

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  1. Data Visualization - Wikipedia. Broad overview of the field of data visualization, its history from William Playfair to modern interactive dashboards, and the principles for representing data visually.

  2. Edward Tufte - Wikipedia. Biography and contributions of Edward Tufte, the leading authority on data visualization whose work on the data-ink ratio, chartjunk, and the 4S model forms the theoretical foundation of this chapter.

  3. Chartjunk - Wikipedia. Defines chartjunk -- unnecessary or distracting visual elements in charts -- and explains Tufte's principle that every element in a visualization should serve the data, not decoration.

  4. Tufte, E. The Visual Display of Quantitative Information. Graphics Press, 2001. The seminal work on data visualization, introducing the data-ink ratio, chartjunk, and principles for displaying data with integrity and clarity. This is the primary source for the visualization theory taught in this chapter.

  5. Few, S. Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press, 2012. Practical guide to choosing the right chart type, designing effective tables, and avoiding common visualization mistakes -- directly supporting the chart selection and design principles in this chapter.

  6. From Data to Viz: A Decision Tree for Choosing Charts - Data to Viz. Interactive decision tree that guides users from their data type to the most appropriate chart format, an essential practical tool for the chart selection process taught in this chapter.

  7. The Beauty of Data Visualization - David McCandless, TED Talk. McCandless demonstrates how well-designed data visualizations reveal hidden patterns and make complex datasets accessible, illustrating the power of visual communication.

  8. Data Visualization Catalogue - Severino Ribecca. Comprehensive reference of chart types organized by function (comparison, distribution, relationship, composition), with examples and guidance for when to use each type.

  9. Misleading Graphs and Statistics - Statistics How To. Catalog of common ways graphs mislead audiences through truncated axes, scale manipulation, cherry-picked data, and other distortions -- directly supporting the ethical visualization topics in this chapter.

  10. Storytelling with Data - Cole Nussbaumer Knaflic. Website and resources from the author of Storytelling with Data, offering practical lessons on using data visualization to communicate findings clearly and persuasively to business audiences.