What do you understand by the term "regression line"?

The term "regression line" refers to a statistical method used to model the relationship between one or more independent variables and a dependent variable. More specifically, when a regression line is plotted on a graph, it visually represents the predicted trend based on the values of the independent variables. This line is derived from a regression analysis, where the objective is to find the best-fitting line that minimizes the distance (or errors) between the actual data points and the line itself.

In this context, the regression line indicates how changes in the independent variable(s) are expected to influence the dependent variable. It allows for predictions and insights based on the identified relationship, which is a fundamental aspect of data-driven decision-making. By understanding this relationship, analysts can forecast outcomes and make informed decisions based on the data.

The other options do not accurately capture the essence of a regression line. For instance, while a regression line can be visually represented, it's more than just a visual representation of variances, and it doesn’t specifically illustrate averages or standard deviations. Instead, it focuses on how one variable predicts or explains changes in another variable within a statistical model.