On the Options
tab of the Predict for Binary Logistic
dialog, specify the confidence intervals.
- Confidence level
Enter the level of confidence for the confidence intervals for the probabilities.
Usually, a confidence level of 95% works well. A 95% confidence level indicates that if you took 100 random samples from the population, the confidence intervals for approximately 95 of the samples would contain the parameter that the interval estimates. For a given set of data, a lower confidence level produces a narrower interval, and a higher confidence level produces a wider interval.
- Type of interval
- You can select a two-sided interval or a one-sided bound. For the same confidence level, a bound is closer to the point estimate than the interval. The upper bound does not provide a likely lower value. The lower bound does not provide a likely upper value.
- Two-sided: Use a two-sided confidence interval to estimate both likely lower and upper values for the probability of the event.
- Lower bound: Use a lower confidence bound to estimate a likely lower value for the probability of the event.
- Upper bound: Use an upper confidence bound to estimate a likely lower value for the probability of the event.