Linear Regression Calculator
Sample data format: Enter one number per line for each variable.
Both variables must have the same number of values.
y = mx + b
0
0
0
Understanding Linear Regression
Linear regression finds the best-fitting straight line through a set of points:
- Slope (m): Rate of change in y relative to x
- Y-intercept (b): Value of y when x = 0
- R-squared: Measure of fit (0 to 1)
Interpreting Results
- Positive slope: Variables increase together
- Negative slope: As one increases, other decreases
- R² near 1: Strong linear relationship
- R² near 0: Weak linear relationship
Common Applications
- Trend analysis
- Sales forecasting
- Scientific research
- Economic modeling
- Quality control