Distribution Analysis (Arbitrarily Censored Data)
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When your data consist of exact failures and a varied censoring scheme, including right-, left- and interval-censored data, your data is arbitrarily-censored. For general information on life data and censoring, see Distribution Analysis Data.

You can enter up to 50 samples per analysis. Minitab estimates the functions independently for each sample, unless you assume a common shape (Weibull) or scale (other distributions). All the samples display on a single plot, with different colors and symbols, which helps you compare the various functions between samples.

Minitab analyzes systems with one cause of failure or multiple causes of failure. For systems that have more than one cause of failure, see Multiple Failure Modes (Arbitrarily Censored Data).

Enter your data in table form, using a Start column and End column:

For this observation...

Enter in the Start Column...

Enter in the End Column...

Exact failure time

Failure time

Failure time

Right censored

Time that the failure occurred after

Missing value symbol '*'

Left censored

Missing value symbol '*'

Time before which the failure occurred

Interval censored

Time at start of interval during which the failure occurred

Time at end of interval during which the failure occurred

 

This data set illustrates tabled data. For observations with corresponding columns of frequency, see Using frequency columns.

Start

End

 

*

10000

Left censored at 10000 hours.

10000

20000

 

20000

30000

 

30000

30000

Exact failures at 30000 hours.

30000

40000

 

40000

50000

 

50000

50000

 

50000

60000

Interval censored between 50000 and 60000 hours.

60000

70000

 

70000

80000

 

80000

90000

 

90000

*

Right censored at 90000 hours.

When you have more than one sample, you can use separate columns for each sample. Alternatively, you can stack all the samples in one column, then set up a column of grouping indicators, which can be numbers or text. For an illustration, see Stacked vs. Unstacked data.