About Quadratic Regression
Quadratic regression is a statistical method for finding the equation of a parabola that best fits a set of data points. This powerful analysis technique models relationships where the rate of change is itself changing, creating a curved (parabolic) relationship between variables.
y = ax² + bx + c
The quadratic regression equation includes these components:
- a - Determines the parabola's curvature (concave up if positive, concave down if negative)
- b - Controls the linear component of the relationship
- c - Represents the y-intercept of the parabola
- R² (R-squared) - Measures goodness of fit (0 to 1, where 1 indicates perfect fit)
Our quadratic regression calculator requires at least 3 data points to compute an accurate parabola equation. For best results, provide a range of x-values that adequately represent the relationship you're modeling.
Common Applications of Quadratic Regression:
- • Physics: Projectile motion and acceleration analysis
- • Economics: Cost/profit optimization models
- • Biology: Population growth and enzyme kinetics
- • Engineering: Structural load distribution
- • Meteorology: Temperature change patterns
- • Finance: Risk assessment models
How to Use This Quadratic Regression Tool:
- Enter your x and y data points in the input fields
- Click "Add Point" for each data pair
- When you have at least 3 points, click "Calculate Regression"
- View your quadratic equation and R-squared value
- Analyze the visual graph of your data and regression curve