The line of best fit is defined to be that line with the property that the sum of the squares of the vertical distances of the y coordinates of the data points from the line is a minimum.

When the data do seem to follow a basic linear pattern we try to "fit a line" to the data. We want to draw the line so that it follows the same upward or downward trend as the data points. The line need not pass through any of the data points exactly, but it should roughly balance out the points that lie above the line with the points that lie below it. A line whose purpose is to model the data in this way is referred to as a line of best fit.

A line of best fit is a line that approximates between a group of ordered pairs. Use the steps below to find the equation of the line of best fit.

Step 1: Graph the ordered pairs to create a scatter plot.
Step 2: Use a ruler to draw a line of best fit. Some points may be on the line and others may not.
Step 3: Choose two points on the line drawn. Use the formula $m = \frac{y_{2}-y_{1}}{x_{2}-x_{1}}$ to find the slope of the line.
Step 4: Find the y-intercept by substituting the x-coordinate of one point, the y-coordinate of the same point and the slope in the formula y = mx+b. Then solve for b.
Step 5: Write the equation of the line of best fit in slope - intercept form.