For some given points, can you find the "line of best fit"?

One method involves finding the line for which the sum of the squares is least.

Change the values for the gradient (m) and the y-intercept (c) to find the line

which gives the least value for the sum of the squares shown.

Now try moving the points A, B, C and D and see how this affects the line of best fit!

And for some more interesting statistics, feel free to play and explore...