Choose , select the distribution, then enter the parameters.

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

- In First shape parameter, enter a number that is greater than zero for the first shape parameter.
- In Second shape parameter, enter a number that is greater than zero for the second shape parameter.

For example, this plot shows a beta distribution that has a first shape of 3 and a second shape of 2.

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 of interest 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.

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

- In Location, enter a value that represents the location of the peak of the distribution.
- In Scale, enter a value that represents the spread of the distribution.

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

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

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

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, the 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.

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 calculate the cumulative probability or the inverse cumulative probability, in Noncentrality parameter, enter the noncentrality parameter. Usually, the noncentrality parameter is 0.

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 Gamma distribution.

- In Shape parameter, enter the value that represents the shape of the distribution.
- In Scale parameter, enter the value that represents the scale of the distribution.
- In Threshold parameter, enter the lower bound of the distribution.

For example, this plot shows a gamma distribution that has a shape of 3, a scale of 1, and a threshold of 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 occurrence on each trial. An occurrence is called an "event".
- To specify which version of the geometric distribution to use, click Options, and select one of the following:
- Model the total number of trials: Model the total number of trials that are needed to produce one event.
- Model only the number of non-events: Model the number of nonevents that occur before one event occurs.

###### Tip

To change the default settings for future sessions of Minitab, choose

.

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

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

- In Population size (N), enter the total number of items in the population (N). When N is too large to be known, the binomial distribution approximates the hypergeometric distribution.
- In Event count in population (M), enter a number between 0 and N (population size) to represent the number of events in the population.
- In Sample size (n), enter the number of items that are sampled without replacement.

For example, this plot shows a hypergeometric distribution that has a population of 400, an event count of 10, and a sample size of 40.

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 of 1 and a maximum of 6.

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

- In Location, enter a value that represents the location of the peak of the distribution.
- In Scale, enter a value that represents the spread of the distribution.

For example, this plot shows a Laplace distribution that has a location of 0 and a scale of 1.

Complete the following steps to enter the parameters for the largest extreme value distribution. For more information, go to Smallest and largest extreme value distributions.

- In Location, enter a value that represents the location of the peak of the distribution.
- In Scale, enter a value that represents the spread of the distribution.

For example, this plot shows a largest extreme value distribution that has a location of 0 and a scale of 1.

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

- In Location, enter a value that represents the location of the peak of the distribution.
- In Scale, enter a value that represents the spread of the distribution.

For example, this plot shows a logistic distribution that has a location of 0 and a scale of 1.

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

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

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

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 that has a location of 0, a scale of 1, and a threshold of 0.

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

- In Event probability, enter a number between 0 and 1 for the probability of occurrence on each trial. An occurrence is called an "event".
- In Number of events needed, enter a positive integer that represents the number of times the event must occur.
- To specify which version of the negative binomial distribution to use, click Options, and select one of the following:
- Model the total number of trials: Model the total number of trials that are needed to produce the specified number of events.
- Model only the number of non-events: Model the number of nonevents that occur before the specified number of events occur.

###### Tip

To change the default settings for future sessions of Minitab, choose

.

For example, this plot shows a negative binomial distribution that models the total number of trials, and has an event probability of 0.5 and 5 events.

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 value for 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.

Complete the following steps to enter the parameters for the smallest extreme value distribution. For more information, go to Smallest and largest extreme value distributions.

- In Location, enter a value that represents the location of the peak of the distribution.
- In Scale, enter a value that represents the spread of the distribution.

For example, this plot shows a smallest extreme value distribution that has a location of 0 and a scale of 1.

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 calculate the cumulative probability or the inverse cumulative probability, in Noncentrality parameter, enter the noncentrality parameter. Usually, the noncentrality parameter is 0.

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

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

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

For example, this plot shows a triangular distribution that has a lower end point of 10, a mode of 50, and an upper end point of 100.

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 value that represents the shape of the distribution.
- In Scale parameter, enter the value that represents the scale of the distribution.
- In Threshold parameter, enter the lower bound of the distribution.

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