Data visualization is not merely the creating of charts from a set of data. It is about bringing the key insights and information from the analysis of a set of data to life for the stakeholder and$/$or decision maker. The tools and charts don't know what the critical questions are, who your audience is$,$ or what decision is being made. That's your job as an analyst. Two leading data visualizers are David McCandless and Nathan Yau. Read Yau's "Data Point" chapter and watch the video on the "Beauty of Data Visualization".

What are some examples from your professional or academic life that are an extremely poor use of graphs to communicate the important points from a set of data? What information from these resources stood out to you to make data visualizations more effective for decision$-$making?

Tools don't know your "data story". What did you learn that will make you personally a more effective communicator with data?

Explain the principle of proportional ink regarding the data$-$to$-$ink ratio and the importance of this principle in presenting data$-$based information graphically.

How does the principle of proportional ink apply to some of the most commonly used types of graphs, such as bar charts, bubble charts, etc.?

What are common failure modes associated with not applying this data$-$to$-$ink ratio principle in data visualizations?

From either the media or your work, identify an example graphic where too much ink was used to bias $($intentionally or unintentionally$)$ the insights gleaned by the audience. How did the amount of ink influence the takeaway from the chart or graph?

Consider the quote from Nathan Yau, "The connection between data and what it represents is key to visualization that means something." What are key contextual elements that should be communicated or included with any data visualization to effectively communicate to the audience what the data actually represents $($and what it does not represent$)?$

In addition to a poor data$-$to$-$in ratio, identify and explain other failure modes that are common with the use of data visualizations to communicate insights from data.

Discuss, at a minimum, the use of logarithmic scales, bar charts with axes that fail to reach zero, and the famous pie chart.