Interpret the key results for Cumulative Distribution Function (CDF)

The cumulative distribution function (CDF) calculates the cumulative probability for a given x-value. Use the CDF to determine the probability that a data value is less than or equal to a certain value, higher than a certain value, or between two values.

For a continuous distribution, Minitab calculates the area under the probability density function, up to an x-value that you specify.

Cumulative Probability
x
P(X ≤ x)
Key Results: x and P(X ≤ x) for a continuous distribution

In these results, suppose you assume that soda can fill weights are normally distributed with a mean of 12 ounces and a standard deviation of 0.25. The cumulative probability that a randomly chosen can of soda has a fill weight that is less than or equal to 11.5 ounces is 0.022750. The cumulative probability that a randomly chosen can of soda has a fill weight that is less than or equal to 12.5 ounces is 0.977250.

For a discrete distribution, Minitab calculates the cumulative probability values for the x-values that you specify.

Cumulative Probability
x
P(X ≤ x)
Key Results: x and P(X ≤ x) for a discrete distribution

In these results, suppose you assume that you roll a fair die. You have a discrete integer probability of 1/6 for rolling each of the sides (1-6). The cumulative probability that you roll a 3 or less is 0.50000. The cumulative probability that you roll a 4 or less is 0.66667, and the cumulative probability that you roll a 6 or less is 1.00000.

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