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Ordinary least squares [OLS]

By Jim Frost

Ordinary least squares, or linear least squares, estimates the parameters in a regression model by minimizing the sum of the squared residuals. This method draws a line through the data points that minimizes the sum of the squared differences between the observed values and the corresponding fitted values.

Related

Synonyms:
Linear least squares
Related Articles:
  • Heteroscedasticity in Regression Analysis
  • Choosing the Correct Type of Regression Analysis
  • Confounding Variables Can Bias Your Results
  • 7 Classical Assumptions of Ordinary Least Squares (OLS) Linear Regression
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