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Lesson Plan: Linear Regression

This lesson plan includes the objectives, prerequisites, and exclusions of the lesson teaching students how to find and use the least squares regression line equation.


Students will be able to

  • understand how the least square regression line (alternatively, the regression line or line of best fit) is defined,
  • interpret the slope (or gradient) of the regression line,
  • graph the scatter plot and the regression line on the same grid,
  • use the equation of the least square regression line to solve real-life situations,
  • understand that the regression line is used to predict the value of the dependent variable from a given value of the independent variable (and not the other way round),
  • predict the value of 𝑦 using the regression model,
  • understand that linear regression is not valid for extrapolation,
  • provide reasons for when correlation can suggest causation based on the real-world context.


Students should already be familiar with

  • sampling methods,
  • scatter diagrams,
  • the direction of correlation,
  • the strength of correlation,
  • causality,
  • graphing an equation of a line.


Students will not cover

  • the formula for the gradient and 𝑦-intercept of the regression line,
  • the correlation coefficient,
  • computing residuals, variation, and 𝑅,
  • the statistical symbol (hat) for predictors.

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