A least squares regression line is a line that represents the relationship between variables in a scatterplot. It is also known as the line of best fit or a trend line. The procedure fits the line to the data points in a way that minimizes the sum of the squared vertical distances between the line and the data points. Least squares regression lines are a specific type of model that analysts frequently use to display relationships in their data. The least squares regression line is the line that best fits the data in the sense of minimizing the sum of the squared errors/10%3A_Correlation_and_Regression/10.04%3A_The_Least_Squares_Regression_Line). The line is calculated using the formulas for slope and y-intercept, which are based on the sum of squares of the x and y variables/10%3A_Correlation_and_Regression/10.04%3A_The_Least_Squares_Regression_Line). The least squares regression line is used to predict the behavior of dependent variables and provides a visual demonstration of the relationship between variables. Traders and analysts can use the least squares method to identify trading opportunities and economic or financial trends.