Line of Best Fit — SAT Math Explained
A line drawn through a scatterplot that best represents the trend in the data, minimizing the overall distance between the line and all data points. Also called a trend line or regression line.
The Core Idea
The line of best fit summarizes the linear relationship in a scatterplot into a single equation, enabling prediction. The slope and y-intercept of this line carry real meaning in context.
Key Vocabulary
The line that minimizes the sum of squared vertical distances from each point to the line
Using the line to predict a value within the range of observed data — generally reliable
Using the line to predict beyond the observed data range — less reliable
The vertical distance between an actual data point and the line (actual - predicted)
Interpreting The Equation
The rate of change — for each 1-unit increase in x, y changes by this amount (in context!)
The predicted value of y when x = 0 — may or may not be meaningful in context
Making Predictions
Substitute the x-value into the equation of the line
Calculate the predicted y-value
Note whether this is interpolation (more reliable) or extrapolation (less reliable)
Common Errors to Avoid
Drawing the line through only 2 points rather than the overall trend
Not interpreting slope and intercept in context (just saying 'slope = 2.5' without explaining what it means)
Over-trusting extrapolated predictions
Practice: Line of Best Fit
5 SAT-style questions. Select your answer and get an instant explanation.
The line of best fit is used primarily to:
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