# Documentation

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## Polynomial Curve Fitting

This example shows how to fit a polynomial curve to a set of data using `polyfit`. Use the `polyfit` function to find the coefficients of a polynomial that fits a set of data in a least-squares sense using the syntax

```p = polyfit(x,y,n), ```

where:

• `x` and `y` are vectors containing the `x` and `y` data to be fitted

• `n` is the degree of the polynomial to return

Consider the x-y test data

```x = [1 2 3 4 5]; y = [5.5 43.1 128 290.7 498.4]; ```

Use `polyfit` to find a third-degree polynomial that approximately fits the data.

```p = polyfit(x,y,3) ```
```p = -0.1917 31.5821 -60.3262 35.3400 ```

After you obtain the polynomial using `polyfit`, use `polyval` to evaluate the polynomial at other points that might not have been included in the original data.

Compute the values of the `polyfit` estimate over a finer domain and plot the estimate over the real data values for comparison.

```x2 = 1:.1:5; y2 = polyval(p,x2); plot(x,y,'o',x2,y2) grid on ```