Enter your data for Parametric Distribution Analysis (Arbitrary Censoring)

Stat > Reliability/Survival > Distribution Analysis (Arbitrary Censoring) > Parametric Distribution Analysis

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Enter your data
Assumed distribution

Enter your data

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

Assumed distribution

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.