Answer:
a. error
Explanation:
Vertical Distance: In statistics, when dealing with regression or estimation problems, we often use the concept of vertical distance to measure how far apart the actual values of a dependent variable (Y) are from the estimated values of Y based on a model or prediction.
Error: The vertical distance between the actual value of Y and the estimated value of Y is referred to as the "error." It represents the deviation or the difference between the observed data points and the values predicted by a model or an estimation technique.
Mean: The mean is a measure of central tendency, typically referring to the average of a set of values. It doesn't directly describe the vertical distance between actual and estimated values.
Slope: Slope refers to the steepness of a line in a linear regression model. It indicates how much the dependent variable changes for a unit change in the independent variable. While slope is related to the concept of error in regression, it's not the term used to describe the vertical distance itself.
Regression: Regression is a statistical method used to model the relationship between variables. It involves finding the best-fitting line or curve that minimizes the errors between observed data points and predicted values. However, "regression" itself is not the term used to describe the vertical distance.
In summary, the vertical distance between the actual value of Y and the estimated value of Y is known as the "error." Therefore, the correct answer is option a. "error."