Specify the prediction options for Warranty Prediction

Stat > Reliability/Survival > Warranty Analysis > Warranty Prediction > Prediction
Predict failures through the following time period:
Enter a constant that represents the number of future time periods for which to predict failures. The units of these time values must be the same as those used in the transformed warranty data.
Future Production Schedule - Production quantity for each time period
Enter a constant or constants that indicate the projected quantity of units that will be produced and shipped periodically in the subsequent time periods. If you enter a single constant, Minitab assumes that the quantity shipped is the same for each time period. If the number shipped differs across time periods, enter a separate constant for each time period.
Confidence level

Enter a confidence level between 0 and 100. Usually a confidence level of 95% works well. A 95% confidence level indicates that you can be 95% confident that the interval contains the true population parameter. That is, if you collected 100 random samples from the population, you could expect approximately 95 of the samples to produce intervals that contain the actual value for the population parameter (if all the data could be collected and analyzed).

A lower confidence level, such as 90%, produces a narrower confidence interval and may reduce the sample size or testing time that is required. However, the likelihood that the confidence interval contains the population parameter decreases.

A higher confidence level, such as 99%, increases the likelihood that the confidence interval contains the population parameter. However, the test may require a larger sample size or a longer testing time to obtain a confidence interval that is narrow enough to be useful.

Confidence interval

From the drop-down list, indicate whether you want Minitab to display a two-sided confidence interval (Two-sided) or a one-sided confidence interval (Lower bound or Upper bound). A one-sided interval generally requires fewer observations and less testing time to be statistically confident about the conclusion. Many reliability standards are defined in terms of the worst-case scenario, which is represented by a lower bound.


The confidence level that you enter applies to all of the confidence intervals in the results.

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