A confidence interval gives a range of plausible values for a population parameter
The center of the interval is usually the sample estimate
The lower and upper bounds show the uncertainty around that estimate
A wider interval means less precision
A narrower interval means more precision
A 95% confidence interval means the method used would capture the true parameter about 95% of the time in repeated samples
A confidence interval does not mean there is a 95% probability that the true parameter is inside one specific interval
If the interval includes the null value, the result may not be statistically significant at that confidence level
If the interval excludes the null value, the result may be statistically significant at that confidence level
The interval should be interpreted in the context of the data, sample size, and variability
Confidence intervals help assess both statistical significance and practical importance
Overlapping confidence intervals do not always mean there is no meaningful difference
Confidence intervals are more informative than a single point estimate alone