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Data Visualization

  1. Data visualization is the strongest tool of what we call exploratory data analysis.
  2. John Tukey, considered the father of exploratory data analysis once said, the greatest value of a picture is when it forces us to notice what we never expected to see. We note that many widely used data analysis tools were initiated by discoveries made with exploratory data analysis. Exploratory data analysis is perhaps the most important part of data analysis, yet it is often overlooked. Data visualization is also now pervasive and philanthropic in educational organizations.
  3. One example comes from GAPminder and the talks, New Insights on Poverty and the Best Stats You've Ever Seen, Hans Roslings forced us to notice the unexpected with a series of plots related to world health and economics.
  4. In his videos, he used animated graphs to show us how the world was changing, and how old narratives are no longer true.
  5. It is also important to note that mistakes, biases, systematic errors, and other unexpected problems often lead to data that should be handled with care. Failure to discover these problems often leads to flawed analyses
  6. and false discoveries.
  7. As an example, consider that measurement devices sometimes fail and that most data analysis procedures are not designed to detect these yet. These data analysis procedures will still give you an answer. 
  8. The fact that it can be hard or impossible to notice an error just from the reported results makes data visualization particularly important.
--
Deepesh Rajpal | c: 98282.38079 | rajpal.deepesh@gmail.com

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