LSRL (Least Squares Regression Line)
Definition
The LSRL, also known as the least squares regression line, is a straight line that best represents the relationship between two variables by minimizing the sum of squared residuals. It is commonly used to predict values based on observed data points.
Analogy
Imagine you have scattered puzzle pieces on your table and you want to draw a straight line through them in such a way that minimizes how far each piece is from the line. The LSRL is like drawing that perfect line through all those puzzle pieces.
Related terms
Residuals: The differences between observed data points and predicted values on the LSRL.
Correlation Coefficient (r): A measure of how closely related two variables are; it ranges from -1 to 1.
Extrapolation: Using the LSRL to make predictions outside of the range of observed data points.
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