1. Starting with the points in their original positions, choose "manipulate a line" and try to fit a line to the data on the graph by either dragging the line, using the sliders, or typing.

    One popular way to compute a best fit line is to minimize the sum of the squares of the difference between the data points and the line. This approach is known as "least squares fit."

  2. Turn on the "show error squares" option, note the total error, then try to minimize it by adjusting your trial line.

  3. To see the actual least-squares fit line, select "compute least squares fit line."

    • How does this compare to your trial line?
    • To see the least squares error, snap the trial line to the least squares line using the button next to right of the equation of the (green) trial line.

  4. Turn off the "compute least squares fit line" and "show error squares" options. Drag the left most point to the lower left part of the graph area and repeat steps 1 - 3 above.

    • What can you say about the effect of extreme data points on the usefulness of the least squares approach?