Line of Best Fit
Plot a set of data and determine a line of best fit.
Plot points by clicking anywhere on the grid, or plot a set of points by entering a pair of coordinates in the text box and clicking
box and click on any point to remove it. You can also click‑and‑drag any point to change its location.
When you check the box for
, a purple line will appear on the grid. Drag the purple dots to approximate a line of best fit visually. An equation of this line will appear to the right. A slope and y-intercept can also be entered to change the line of best fit. When you check the box for
Show Line of Best Fit
, the area least-squares regression line will be displayed. An equation of this line and the correlation coefficient (
) will appear.
The grid can be zoomed in and out as more points are added. Use the
magnifying glass to zoom. To see a different portion of the grid, highlight the
box and use the mouse to drag the graph around. You can reset the original parameters for the graph or use the
Zoom to Fit
box to have the graph automatically select parameters that will show all your points optimally.
The data below shows the points scored and minutes played by the six "starters" for the Los Angeles Lakers during the 2004-05 season. (For this investigation, a "starter" is any player who averaged more than 20 minutes per game.)
Plot points scored along the horizontal axis and minutes along the vertical axis.
box to see a linear approximation of this data. The correlation coefficient (
) indicates how well the line approximates the data. If |
| = 1, the line is a perfect fit to the data; if |
| = 0, the line does not fit the data at all. In general, the closer |
| is to 1, the better the fit.
You can conduct similar investigations for other sports by looking at the statistics for Major League Baseball (MLB), National Football League (NFL), Women's National Basketball Association (WNBA), Major League Soccer (MLS), or other sports that interest you.