The Method
x={1,2.7,3.2,4.8,5.6}
y={14.2,17.8,22,38.3,51.7}We can use a Lagrangian polynomial of degree 4, P4. The following function will return the Lagrangian polynomial of degree one less than the number of points. By the way, if you want a lesser degree, simply disregard some of the points.
lagrangepoly[t_,x_,y_]:=
Module[{n,poly,q,i,j},
n=Dimensions[x][[1]];poly=0;
For[i=1,i<=n,i++,
q=1;
For[j=1,j<=n,j++,
If[j!=i,q=q*(t-x[[j]])/(x[[i]]-x[[j]])]
];
poly=poly+q*y[[i]];
];
poly
];
p4[t_]:=lagrangepoly[t,x,y]
p4[t]
Do you trust the Lagrange polynomial? Let's evaluate it at the x values and see if the match the y values.
test=p4[x] y
To convince you that the Lagrange polynomial is an easy way to fit points, let's look more closely at its definition:
x={x1,x2,x3,x4,x5}
y={y1,y2,y3,y4,y5}
p4[t_]:=lagrangepoly[t,x,y]
p4[t]
Now do you see why this works? (And works easily!)