If you have exact failure times, right-censored observations (you know only the time after which the failure occurred), or both, complete the following steps. For more information on censored data, go to Data censoring.
C1 | C2 | C3 |
---|---|---|
Time | Censor | Temperature |
53 | F | 125 |
60 | F | 125 |
53 | F | 125 |
99 | C | 125 |
51 | F | 150 |
40 | F | 150 |
If your data include left-censored observations (you know only the time before which the failure occurred), interval-censored observations (you know only the times between which the failure occurred), or a varied censoring scheme that includes exact failure times, right censoring, left censoring, and interval censoring, complete the following steps. For more information on censored data, go to Data censoring.
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 |
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 |
C1 | C2 | C3 | C5 |
---|---|---|---|
Start | End | Frequency | Temperature |
* | 10000 | 20 | 125 |
10000 | 20000 | 10 | 125 |
20000 | 30000 | 10 | 125 |
30000 | 30000 | 2 | 125 |
30000 | 40000 | 26 | 125 |
40000 | 50000 | 42 | 125 |
50000 | * | 190 | 125 |
* | 10000 | 22 | 150 |
10000 | 20000 | 14 | 150 |
20000 | 30000 | 15 | 150 |
30000 | 40000 | 33 | 150 |
40000 | 50000 | 55 | 150 |
50000 | * | 161 | 150 |
Minitab assumes that any variable in the model is a covariate unless the variable is specified as a factor. Therefore, if any predictors are factors, you must enter them again in Factors (optional).
Life data models in Minitab must be full rank and hierarchical. For more information, go to Restrictions on models for regression with life data.
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.