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Danger of Summary Metrics

It can be misleading to only look at the summary metrics of data sets.

Danger of Summary Metrics

To demonstrate the effect, statistician Francis Anscombe put together four example data sets in the 1970s. Known as Anscombe’s Quartet, each data set has the same mean, variance and correlation. However, when graphed, it’s clear that each of the data sets are totally different. The point that Anscombe wanted to make is that the shape of the data is as important as the summary metrics and cannot be ignored in analysis.

Related Reading:

Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing Download the Datasaurus: Never trust summary statistics alone; always visualize your data Summary Statistics Tell You Little About the Big Picture Anscombe’s Quartet, and Why Summary Statistics Don’t Tell the Whole Story Al Gore’s New Movie Exposes The Big Flaw In Online Movie Ratings