What is the difference between confidence intervals and prediction intervals?

The confidence intervals tell you how well you have determined the mean. Assume that the data is random. If you do this many times, you’d expect about 95 percent of the intervals to include the true value of the population mean. The key point is that the confidence interval tells you the location of the true population.

Predicting intervals tell you where you can expect to see the next data point. The data might be from a random distribution. Take a sample of data and make a prediction interval. You should sample one more value from the population. The key point is that the prediction interval tells you about the distribution of values, not the uncertainty in determining the population mean, if you do this many times.

Predicting intervals have to account for the uncertainty in knowing the population mean and scatter. A prediction interval is bigger than a confidence interval.