Calculating probabilities for different distributions

You can calculate values for probability density functions, cumulative distribution functions, or inverse cumulative probabilities of your data, for the distribution you choose from the menu.
  • The probability density function (PDF) is the curve for the distribution. For example, a PDF can describe the distribution of tree diameters in a forest.
  • The cumulative distribution function (CDF) for any value x gives the cumulative probability associated with a probability distribution function. Specifically, a CDF gives the cumulative area under the PDF, up to the value you specify. For example, a CDF can indicate the proportion of trees in the forest that are at least ten inches in diameter.
  • The inverse cumulative probability (ICDF) is the value associated with an area. It is the reverse of the CDF, which is the area associated with a value. For example, an inverse cumulative probability can indicate how wide 75% of the trees are.
Here is a visualization of these concepts:

Use PDF when you know x and want the corresponding y-value on the curve.


Use CDF when you know x and want the area under the curve.


Use ICDF when you know the cumulative area under the curve and want the x-value.

For discrete distributions (Bernoulli, binomial, geometric, negative binomial, hypergeometric, discrete, integer, and Poisson), Minitab calculates the discrete probability function. For continuous distributions, such as the normal distribution, Minitab calculates the continuous probability density function (also called the density function).

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