Select the option that best describes your data.

Complete the following steps if your data are in a column of the worksheet.

- From the drop-down list, select Sample data are in a column.
- In Sample, enter the column of data that you want to analyze. The column must contain two distinct values, such as True and False.
- In Event, select the outcome that Minitab uses as the event (also called success). The sample proportion equals the number of events divided by the total number of trials.
- In Number of resamples, enter the number of times Minitab should take resamples of your data. The sample size for each resample is equal to the sample size of the original dataset. You can enter any value from 1 to 10,000. Usually, a large number of resamples works best.
- Enter a value in Hypothesized proportion. The Hypothesized proportion defines your null hypothesis (H
_{0}: ρ = ρ_{0}). Think of this value as a target value or a reference value. For example, an analyst enters 0.043 to determine whether the proportion of customers that respond to a direct-mail offer is different from 4.3% (H_{0}: p = 0.043).

In this worksheet, Purchase is the sample and indicates whether a household made a purchase after receiving an advertisement. The event is Yes.

C1 |
---|

Purchase |

Yes |

No |

No |

No |

Complete the following steps if you know the number of events and trials, and do not have actual sample data in the worksheet.

- From the drop-down list, select Summarized data.
- In Number of events, enter the number of successes. For example, if you want to determine the proportion of defective parts, the number of events would equal the number of defective parts.
- In Number of trials, enter the total number of observations. For example, if you want to determine the proportion of defective parts, the number of trials would equal the total number of parts that you sampled.
- In Number of resamples, enter the number of times Minitab should take resamples of your data. The sample size for each resample is equal to the sample size of the original dataset. You can enter any value from 1 to 10,000. Usually, a large number of resamples works best.
- Enter a value in Hypothesized proportion. The Hypothesized proportion defines your null hypothesis (H
_{0}: ρ = ρ_{0}). Think of this value as a target value or a reference value. For example, an analyst enters 0.043 to determine whether the proportion of customers that respond to a direct-mail offer is different from 4.3% (H_{0}: p = 0.043).