Visualizing Data for Impact: Analyzing Misleading Visualizations

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. One of the challenges of data visualization is recognizing and avoiding misleading visuals. These and other common mistakes make data visualization less effective and can lead to incorrect conclusions. Through this course, learn about misleading statistics and visual distortions. Examine some common data visualization mistakes, including data overload, interchanging charts, and the use of color, as well as how to recognize and correct them. Next, explore examples of deceiving statistics, visual distortions, and graphs and how to avoid being misleading. Finally, learn about omitting data, improper extraction, and correlating causation. After course completion, you'll be able to avoid mistakes when visualizing your data.