# Table of survival probabilities for Regression with Life Data

The table of survival probabilities provides the probability that the product survives until a particular time. Use these values to determine whether your product meets reliability requirements, or to compare the reliability of two or more product designs.

The table of survival probabilities consists of the following columns:
• Time, which is the particular time until a certain probability of the product is predicted to survive.
• Predictors, which indicate the combination of factor settings for that prediction.
• Probability, which is the chance that the product will survive until a particular time.
• 95% confidence interval, which provides a range of values that are likely to contain the true value of the parameter.

Use these values only with an appropriate model for the data. If the model fits the data poorly, these estimates may not be accurate.

## Example output

Table of Survival Probabilities 95.0% Normal CI Time Design Weight Probability Lower Upper 240 Standard 5.0 0.753732 0.495880 0.892300 240 Standard 7.5 0.526440 0.305413 0.706746 240 Standard 10.0 0.233138 0.048803 0.495546 240 New 5.0 0.995268 0.973052 0.999177 240 New 7.5 0.989293 0.950941 0.997699 240 New 10.0 0.975865 0.894926 0.994638

## Interpretation

For the compressor data, the table of survival probabilities includes the following results:
• Row 1 refers to the combination of a standard design and projectile weight of five pounds. For this combination, the model predicts that the 240-hour reliability is 0.753752. In other words, there is a 75.3752% chance that a standard compressor case that is subjected to a five pound projectile will survive until 240 hours.
• Row 4 refers to the combination of a new design and projectile weight of five pounds. For this combination, the model predicts that the 240-hour reliability is 0.995268. In other words, there is a 99.5268% chance that a new compressor case that is subjected to a five pound projectile will survive until 240 hours.

By comparing the survival probabilities for the standard and new designs with the same projectile weight, the manufacturer concludes that the new design survives for a longer time than the standard design.

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