In the Cumulative Distribution Function (CDF) dialog box, select the distribution and the parameters.

Complete the following steps to enter the parameters for the binomial distribution.

- In Number of trials, enter the sample size.
- In Event probability, enter a number between 0 and 1 for the probability that the outcome you are interested in occurs. An occurrence is called an "event".

Complete the following steps to enter the parameters for the chi-square distribution.

- In Degrees of freedom, enter the degrees of freedom to define the chi-square distribution.
- If you are calculating cumulative probability or inverse cumulative probability, in Noncentrality parameter, enter the noncentrality parameter. Usually, the noncentrality parameter is 0.

Complete the following steps to enter the parameters for the discrete distribution.

- In Values in, enter the column that contains the values to include in the distribution. Usually, values are discrete events or counts that are represented by numeric values.
- In Probabilities in, enter the column that contains the probabilities for each value. Probabilities must be between 0 and 1, and must sum to 1.

Complete the following steps to enter the parameters for the exponential distribution.

- In Scale, enter the scale parameter. The scale parameter equals the mean when the threshold parameter equals 0.
- In Threshold, enter the lower bound of the distribution.

Complete the following steps to enter the parameters for the F-distribution.

- In Numerator degrees of freedom and Denominator degrees of freedom, enter the numerator and denominator degrees of freedom to define the F-distribution.
- If you are calculating cumulative probability or inverse cumulative probability, in Noncentrality parameter, enter the noncentrality parameter. Usually, the noncentrality parameter is 0.

Complete the following steps to enter the parameters for the Geometric distribution.

- In Event probability, enter a number between 0 and 1 for the probability of an occurrence on each trial. An occurrence is called an "event".
- From Model, select one of the following to specify the number to model.
- Total number of trials: The number of trials includes both events and nonevents.
- Only the number of non-events: Do not count the event.

For example, this plot shows a geometric distribution that has an event probability of 0.5 and models the total number of trials.

Complete the following steps to enter the parameters for the integer distribution.

- In Minimum value, enter the lower end point of the distribution.
- In Maximum value, enter the upper end point of the distribution.

Complete the following steps to enter the parameters for the lognormal distribution.

- In Location, enter a value that represents the location of the peak of the related normal distribution.
- In Scale, enter a value that represents the spread of the related normal distribution.
- In Threshold, enter the lower bound of the distribution.

Complete the following steps to enter the parameters for the normal distribution.

- In Mean, enter the value for the center of the distribution.
- In Standard deviation, enter the value for the spread of the distribution.

In Mean, enter the average rate of occurrence. For more information, go to Poisson distribution.

Complete the following steps to enter the parameters for the t-distribution.

- In Degrees of freedom, enter the degrees of freedom to define the t-distribution.
- If you are calculating cumulative probability or inverse cumulative probability, in Noncentrality parameter, enter the noncentrality parameter. Usually, the noncentrality parameter is 0.

Complete the following steps to enter the parameters for the uniform distribution.

- In Lower endpoint, enter the minimum value for the distribution.
- In Upper endpoint, enter the maximum value for the distribution.

Complete the following steps to enter the parameters for the Weibull distribution.

- In Shape parameter, enter the shape parameter to define the Weibull distribution.
- In Scale parameter, enter the scale parameters to define the Weibull distribution.
- In Threshold parameter, enter the lower bound of the Weibull distribution.