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# Why do data distributions take a particular shape?

Updated: 9/24/2023

Wiki User

9y ago

If you plot data they must take some shape (or another)! Data distributions can take all kinds of shapes. The only constraints are that

• they cannot be negative and
• the integral (sum) over all possible values is 1.

The shapes can be flat (uniform distribution), symmetric (uniform or Gaussian), asymmetric with one peak somewhere in the middle (Poisson), asymmetric with a peak at an end (exponential). These are examples of different shapes that are attained by common continuous data distributions.

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9y ago

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