I have a set of data that fits nicely to a quadratic equation

Since the factors of a quadradic equation can be interpreted as Acceleration + Velocity + Location, I can characterize this data as containing an acceleration component. But this non-linear aspect of the data makes the use of average (and thus standard deviation and other tools that depend on average) of questionable merit.

What is the best practice for examining the spread of quadradic data?

Since the factors of a quadradic equation can be interpreted as Acceleration + Velocity + Location, I can characterize this data as containing an acceleration component. But this non-linear aspect of the data makes the use of average (and thus standard deviation and other tools that depend on average) of questionable merit.

What is the best practice for examining the spread of quadradic data?

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