Final answer:
A regression line, also known as a line of best fit or least-squares regression line, is used to predict the dependent variable (y) from the independent variable (x) in a given data set. To find the regression line, you need to calculate the slope and y-intercept. The equation of the regression line is typically represented as ŷ = mx + b, where m is the slope and b is the y-intercept. You can use this equation to predict the value of y for a given value of x.
Step-by-step explanation:
A regression line, also known as a line of best fit or least-squares regression line, is used to predict the dependent variable (y) from the independent variable (x) in a given data set. To find the regression line, you need to calculate the slope and y-intercept. The equation of the regression line is typically represented as ŷ = mx + b, where m is the slope and b is the y-intercept. You can use this equation to predict the value of y for a given value of x.