Fit y = ax³ + bx² + cx + d line using this calculator

Accepts csv, parquet, arrow, json and tsv

- Upload your dataset
- Select the independent (X) and dependent (Y) variables
- The regression analysis will be performed
- Download, share or embed the results

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Cubic regression is used to fit cubic line of best fit to import data. it is very useful when your input data looks like a cubic function.

You can also perform cubic regression using quadratic regression and an order of 3.

Progression is very useful when the input data looks like a third-order polynomial. We can use cubic regression to find a third order line of best fit to the input data. The cubic regression alcohol or give us the regression coefficients for each Cube x squared x and the constant offset.

Cubic regression models typically have two curves. If one or more of the coefficients is very close to 0 then the cubic regression model may appear to have fewer curves.

The cubic regression calculator fits a cubic equation to the input data

$y = ax^3 + bx^2 + cx + d$

Where y is the response variable and x is the predictor variable.

Cubic regression is a special case of linear regression. The line of best fit is a cubic function. But the cubic regression equation is linear with respect to the coefficients a, b, c, and d.