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This lecture covers the design principles of data visualization, including selecting relevant intervals, ensuring visual integrity, minimizing chart junk, and optimizing the data ink ratio. It emphasizes the importance of choosing appropriate scales, avoiding unnecessary elements that clutter the message, and maximizing the data-to-ink ratio. Examples of common visualization errors and solutions are discussed, such as the impact of color choices, the use of small multiples, and the sensitivity of averages to extreme values.