Polynomial Curve Fitting
Least-squares regression from tabular data
Awaiting data
Curve Visualization
Least-squares regression from tabular data
| Name | Equation | R² | N pts | Opt. deg |
|---|
x and y.Two columns per row, comma or semicolon delimited. A header row is optional and detected automatically.
x,y
-3,8.7
-2,3.9
-1,0.8
0,0.1
1,1.2Separate each series with a blank line. Optionally add a name on the line just above the data.
Measurement A
x,y
0,1.2
1,3.5
2,6.8
Measurement B
x,y
0,0.4
1,1.9
2,4.1Up to 20 series can be loaded at once.
The slider sets the degree d of the fitted polynomial:
Higher degrees fit the data more closely but may overfit noise. Start low and increase until R² stops improving significantly.
R² (coefficient of determination) measures how well the curve fits the data:
Each row in the Series table represents one curve. Click any row to toggle its visibility on the chart. The eye icon on the right also acts as a toggle.
The in-chart legend shows up to 6 series; if more are visible it displays +N more…
The Coefficients section shows the exact polynomial coefficients for each series:
y = a₀ + a₁x + a₂x² + … + aₙxⁿCoefficients are displayed with 8 significant figures.