Lagrange Polynomials

Remarkably, given a collection of points, it's possible to find a relatively small polynomial which passes through those points exactly. This polynomial model is pretty simple and a really good fit for our data (a perfect fit for our data!), which might lead us to believe that it's a good model, potentially useful for making predictions. In this interactive, we'll see that it is not.

Pick a number of data points (n) and enter some data below. If you like, you can click on one of the buttons below to load a prefetched data set.



3/1/19 to 3//19
with points
with points
with points
n:
Show rational coefficients
Draw Points
Label Points
Draw Axes
Label Axes
Draw Grid
Draw Graph

Make Your Own Lagrange Polynomial

Below, I'll walk you through the steps to figure out the lagrange polynomial fitting the data points entered above. It's suggested that you enter a really simple data set with at least three non-colinear integer points such as (0,1),(1,2),(2,4) .