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Covariance VS Correlation

shauryaa117 profile image Shaurya Lalwani ・1 min read

Covariance:

  1. Defines 3 types of relationships: Positive Trend, Negative Trend, and No Relationship
  2. Covariance cannot tell whether the slope of the line representing the mentioned relationship between variables, is steep or not, instead, it will only express whether the slope is positive or negative.
  3. Covariance can change even when the relationship does not, because covariance values are dependent on the scale and that also makes them difficult to interpret.

Correlation:

  1. Correlation shows the strength of the relationship between variables
  2. Correlation is standardized covariance. It does not depend on the scale of the data.
  3. The more data we have, the more confidence we can have in the value of correlation that we obtain with the best fit line/plane

Thanks for reading! Happy learning!
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