From Confidence level, select the level of confidence for the confidence intervals and the prediction intervals.
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 mean response. Similarly, the prediction interval indicates that you can be 95% confident that the interval contains the value of a single new observation.
For a given set of data, a lower confidence level produces a narrower interval, and a higher confidence level produces a wider interval. The width of the interval also tends to decrease with larger sample sizes. Therefore, you may want to use a confidence level other than 95%, depending on your sample size.
- If your sample size is small, a 95% confidence interval may be too wide to be useful. Using a lower confidence level, such as 90%, will produce a narrower interval. However, the likelihood that the interval contains the mean response decreases.
- If your sample size is large, you may want to consider using a higher confidence level, such as 99%. With a large sample, a 99% confidence level may produce a reasonably narrow interval and also increase the likelihood that the interval contains the mean response.