The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.

For example, consider the scatter plot of profit versus investment of a company. These two variables are positively correlated.

The predicted profit for an investment of 920,000 will yield a single value - a point estimate of the profit.

A serious disadvantage of having a point estimate is that it does not contain any information about the accuracy of the value.

So, a prediction interval is used to estimate the range within which this y-value might lie.

The prediction interval depends on the standard error of estimate - a collective measure of the spread in data points around the regression line. A lower s_e-value indicates data points closer to the regression line.

The standard error of estimate is used to calculate the margin of error, which provides the prediction interval for the y-value.