What term describes the signed vertical distance between a data point and a line of best fit?

The signed vertical distance between a data point and a line of best fit is referred to as a residual. In the context of regression analysis, when a line of best fit is drawn through a set of data points, the residual for a given data point is calculated by subtracting the predicted value (as determined by the line of best fit) from the actual observed value of that data point. This distance can be positive or negative, indicating whether the actual data point lies above or below the line.

Understanding the concept of residuals is crucial because they provide insight into how well the line represents the data. If the residuals are small and randomly distributed, it suggests that the line of best fit is a good predictor of the actual data. Conversely, large residuals or patterns in their distribution may suggest that a different model could better describe the data.

The other terms mentioned—error, deviation, and variance—represent different statistical concepts and are not specifically defined as the signed distance from a data point to a line of best fit, which is precisely why the term residual is the correct choice in this context.