📈 Least Squares Regression Line Calculator
Calculate best fit line using least squares method
Data Points (x, y)
How to Use This Calculator
Enter Data Points
Input (x, y) coordinates of your data points. Add more points as needed.
Calculate
Press "Calculate Regression Line" to find the best fit line using least squares method.
View Results
See the regression line equation (y = mx + b) and R² value.
Formula
Slope: m = (nΣxy - ΣxΣy) / (nΣx² - (Σx)²)
Intercept: b = ȳ - mẍ
where ẍ and ȳ are means, n is number of points
About Least Squares Regression Line Calculator
The Least Squares Regression Line Calculator finds the best fit line through data points by minimizing the sum of squared residuals. It calculates the slope, intercept, and R² value.
When to Use This Calculator
- Statistics: Analyze relationships between variables
- Data Analysis: Find trends in data sets
- Science: Model relationships in experiments
- Economics: Predict trends and relationships
Frequently Asked Questions
What is least squares regression?
Least squares regression finds the line that minimizes the sum of squared vertical distances (residuals) from data points to the line. It's the most common method for finding best fit lines.
What is R²?
R² (coefficient of determination) measures how well the regression line fits the data. It ranges from 0 to 1, where 1 means perfect fit and 0 means no linear relationship.