There is no denying the importance of clean data to support the growth of an organization, however, there are clever ways to tap into human heuristic’s that may end up getting you in trouble. Data visualization is a great tool to analyze data but it can also be misleading. Truncated Y-axis, cumulative graphs, and unheeded conventions are some examples of how data visualization may be used to create deluding results. Therefore, you should be careful while designing visualizations and more so when interpreting graphs created by others. According to recent studies, interpreting visualizations, keep your eyes open for common mistakes, dig deeper, find the context and refrain from making snap judgments.
33% of all stats are completely unsubstantiated. (Get it?). Understand the difference between correlation and causation. Don’t get fooled – Dig deep! For more on the topic please visit our blog or contact firstname.lastname@example.org and see how we provide the right data that drives your bottom line.
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