1. Precision: They offer a measure of how precise an estimate is. A narrow CI indicates high precision, whereas a wide CI suggests more variability. 2. Reliability: They help determine the reliability of study results. A 95% CI, for example, means that there is a 95% probability that the population parameter lies within the given range. 3. Comparisons: CIs enable comparisons between different groups, treatments, or interventions, helping researchers make informed decisions.
