Complete the following steps to enter your data. For more information on censored data, go to Data censoring.

- In Start variables, enter the column that contains the start times. You can enter up to 50 columns (for 50 different samples). The start times in the column depend on how the data are censored.
Observation Value in Start column Exact failure time Failure time Right censored Time after which the failure occurred Left censored * (missing value symbol) Interval censored Time at start of interval during which the failure occurred - In End variables, enter the column that contains the end times. You can enter up to 50 columns (for 50 different samples). The end times in the column depend on how the data are censored.
Observation Value in End column Exact failure time Failure time Right censored * (missing value symbol) Left censored Time before which the failure occurred Interval censored Time at end of interval during which the failure occurred - If you have frequency data for each variable, in Frequency columns (optional), enter a column that indicates the number of units for each failure time or censoring time.
- If all the samples are stacked in one column, select By variable and enter a column of grouping indicators.

In this worksheet, the Start column contains the start times and the End column contains the end times. The Frequency column (optional) indicates the number of units that are included in each interval. For example, 20 units are left censored at 10,000 hours. 2 units are exact failures at 30,000 hours. 26 units are interval censored between 30,000 and 40,000 hours. 190 units are right censored at 60,000 hours.

C1 | C2 | C3 |
---|---|---|

Start | End | Frequency |

* | 10000 | 20 |

10000 | 20000 | 10 |

20000 | 30000 | 10 |

30000 | 30000 | 2 |

30000 | 40000 | 26 |

40000 | 50000 | 40 |

50000 | 60000 | 55 |

60000 | * | 190 |

Select a distribution to model your data. Base your decision on process knowledge or use probability plots to evaluate the model fit. For more information, go to Distribution fit for reliability analysis.