02.06 Covariance and Causality

There is also a negative value of covariance. When 2 random variables vary in opposite directions. An example of this would be an increase in iron in am anemic person causes a decrease in tiredness.

And then there is a zero value of covariance. These variables do not vary together or you can say they appear uncorrelated. An example of this is Ice cream and intelligence.

Causality indicates a true relationship between two events. So there is, in essence, a cause and effect relationship established between two variables. So for example and relationship has been established between the correlation of ice cream sales and the outside temperature.  However, a key thing to remember here is correlation does not necessarily mean causation.

So to review,  covariance is a measure of how changes in one variable are associated with changes in a second variable. There can be a positive value of covariance whereas one increases so too does the other, a negative value of covariance, where they changes are in opposing directions and a zero value of covariance says the two values are uncorrelated.

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