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Ordinary Least Squares (OLS)

Ordinary Least Squares (OLS) minimizes the residual sum of squares (RSS). RSS is the sum of each squared residual (residual = the observed Y minus the predicted "on the line" Y).

Also, about the OLS: the average residual is always zero, and the line passes through the point (average X, average Y).

This video by Bionic Turtle explains this method of ordinary least squares (OLS).

Next Lesson

Course: Linear Regression
LESSONS
  • Introduction to Linear Regression
  • Standard Error of Estimate (SEE)
  • Coefficient of Determination (R-Squared)
  • Sample Regression Function (SRF)
  • Ordinary Least Squares (OLS)
  • Standard Error in Linear Regression
  • ANOVA Table in Regression
  • Using LINEST() Function in Excel for Multivariate Regression

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