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Ordinary Least Squares (OLS)

Statistics

This lesson is part 5 of 8 in the course Linear Regression

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).

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‹ Sample Regression Function (SRF)

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Standard Error in Linear Regression ›

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In this Course

  • 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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