Polynomial Regression Calculator
Uncover the relationship between variables by fitting a polynomial regression model to your data. Visualize the curve and understand the equation.
Input Data
Enter your data points and polynomial degree to calculate the regression model.
Enter comma-separated values for the independent variable.
Enter comma-separated values for the dependent variable.
Choose the degree of the polynomial to fit (e.g., 2 for quadratic).
Results
Polynomial Equation:
R-squared Value:
Regression Curve Visualization
Understanding Polynomial Regression
Polynomial Regression is a form of regression analysis in which the relationship between the independent variable (x) and the dependent variable (y) is modeled as an nth degree polynomial. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y, denoted E(y|x).
This tool helps you find the best-fit polynomial equation for your data and visualizes the regression curve. The R-squared value indicates the goodness of fit, with values closer to 1 representing a better fit. Use this tool to analyze trends, make predictions, and understand the underlying relationships in your data.
- Independent Variable (x): The variable that is being manipulated or changed.
- Dependent Variable (y): The variable that is being measured or tested.
- Degree of Polynomial: Determines the complexity of the curve. A degree of 2 creates a quadratic curve, 3 a cubic curve, and so on.
- R-squared: A statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable or variables in a regression model.