Linear Regression Calculator
Uncover the relationship between two variables with our interactive linear regression tool. Visualize your data and find the line of best fit.
Data Input
Enter your data points below to calculate the linear regression line. Please input comma-separated values for both X and Y datasets.
Regression Results
Visualization
Understanding Linear Regression
Linear regression is a powerful statistical tool used to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable.
The equation for linear regression is represented as \( y = mx + c \), where:
- \( y \) is the dependent variable.
- \( x \) is the independent variable.
- \( m \) is the slope of the line, indicating the rate of change of \( y \) with respect to \( x \).
- \( c \) is the y-intercept, the value of \( y \) when \( x = 0 \).
This calculator uses the least squares method to find the line that minimizes the sum of the squares of the vertical deviations from each data point to the line.
Formulae Used:
- Slope (m): \( m = \frac{n(\sum xy) - (\sum x)(\sum y)} {n(\sum x^2) - (\sum x)^2} \)
- Y-intercept (c): \( c = \frac{\sum y - m(\sum x)}{n} \)
Use Cases:
- Predicting sales trends based on advertising expenditure.
- Analyzing the relationship between study hours and exam scores.
- Forecasting stock prices based on market indicators.
- Understanding the impact of temperature on ice cream sales.
Sources: Wikipedia, Math is Fun