Linear Regression

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Linear Regression

  • You can use regression to make a prediction
  • Similar to a correlation, regression numerically describes the relationship between two variables
  • Linear regression figures out how to do optimal guess
  • Line of best fit is also known as a REGRESSION LINE
  • The line with the minimal distance from each data point, 'minimal deviations' from the line. 
  • The result of linear regression is the regression equation.
  • Each equation is determined by: intercept and slope
  • y=a+bx
  • A=intercept B=gradient
  • Prediction errors are known as residuals. E.g predicted score = 60 actual score = 64 residual =


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