Regression Analysis
Understanding relationships between variables through statistical modeling
Simple Linear Regression
Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered an explanatory variable, and the other is considered a dependent variable.
The linear regression model is represented by the equation: Y = β₀ + β₁X + ε
Where:
- Y is the dependent variable
- X is the independent variable
- β₀ is the y-intercept (the value of y when x = 0)
- β₁ is the slope of the line
- ε is the error term
Interactive Visualization
Click on the chart to add data points. The regression line will automatically adjust.
Regression Parameters:
Equation: Y = 1.00X + 0.00