Not every graph and chart accurately represents the data behind it. Watch for these clues to investigate further.
Check the axes and labels before drawing conclusions. 缺失图表, 不准确的, or selective labeling can give 误导 impressions about data behind them. 例如, an axis that isn’t labeled consistently or starts at a seemingly arbitrary number could misrepresent the effect the chart is trying to illustrate.
Watch out for overly complicated charts or visualizations. 通常被称为“垃圾图表”,” unnecessary visual elements—such as extra illustrations, 图标, 视觉效果, or other ornamentation—can be 误导 or distract from more relevant information. 例如, 3-D pie charts are often 误导 because of the viewing angle necessary to create the three-dimensional effect: the slice that appears closest to the viewer could be visually larger than a statistically larger slice that appears further away.
寻找上下文. 一个单一的, isolated data point—such as median prices, 百分比增加, or counts—can lack context to explain whether it’s part of a trend or outlier. Before drawing conclusions from isolated figures, look for more data to place it in proper context. 例如, a dramatic increase in a statistic could signal the start of a new trend or be part of a seasonal effect, which would be apparent if you had data from the same time period for previous years.