In the Generate Random Data dialog box, select a data distribution and enter the parameters.

In Event probability, enter a number between 0 and 1 for the probability that the outcome of interest occurs. An occurrence is called an "event". For more information, go to Bernoulli distribution.

The Bernoulli distribution is a special case of the binomial distribution (the number of trials is always, n=1). For example, this plot shows a binomial distribution that has 1 trial and an event probability of 0.15.

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".

For example, this plot shows a binomial distribution that has 100 trials and an event probability of 0.03.

In Degrees of freedom, enter the number of degrees of freedom that define the chi-square distribution. For more information, go to Chi-square distribution.

For example, this plot shows a chi-square distribution that has 4 degrees of freedom.

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.

In this worksheet, Value contains the counts to include in the distribution and Probability contains the probability of each count.

C1 | C2 |
---|---|

Value | Probability |

0 | 0.03 |

1 | 0.13 |

2 | 0.70 |

3 | 0.10 |

4 | 0.04 |

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.

For example, this plot shows an exponential distribution that has a scale of 1 and a threshold of 0.

In Numerator degrees of freedom and Denominator degrees of freedom, enter the numerator and denominator degrees of freedom to define the F-distribution. For more information, go to F-distribution.

For example, this plot shows an F-distribution that has 1 numerator degrees of freedom and 1 denominator degrees of freedom.

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.

For example, this plot shows an integer distribution that has a minimum value of 1 and a maximum value of 6.

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.

For example, this plot shows a lognormal distribution with a location of 0, a scale of 1, and a threshold of 0.

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.

For example, this plot shows a normal distribution that has a mean of 0 and a standard deviation of 1.

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

For example, this plot shows a Poisson distribution that has a mean of 10.

In Degrees of freedom, enter the degrees of freedom to define the t-distribution. For more information, go to t-distribution.

For example, this plot shows a t-distribution that has 2 degrees of freedom.

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.

For example, this plot shows a uniform distribution that has a lower endpoint of 2.5 and an upper endpoint of 7.5.

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.

For example, this plot shows a Weibull distribution that has a shape of 5, a scale of 5, and a threshold of 0.