Minitab Help 13: Weighted Least Squares

Minitab 18

Minitab®

Galton peas (nonconstant variance and weighted least squares)

  • Perform a linear regression analysis to fit an ordinary least squares (OLS) simple linear regression model of Progeny vs Parent (click "Storage" in the regression dialog to store fitted values).
  • Select Calc > Calculator to calculate the weights variable = \(1/SD^{2}\) and Perform a linear regression analysis to fit a weighted least squares (WLS) model (click "Options" in the regression dialog to set the weights variable and click "Storage" to store fitted values).
  • Create a basic scatterplot< of the data and click Editor > Add > Calculated Line to add a regression line for each model using the stored fitted values.

Computer-assisted learning (nonconstant variance and weighted least squares)

Market share (nonconstant variance and weighted least squares)

  • Perform a linear regression analysis to fit an OLS model (click "Storage" to store the residuals and fitted values).
  • Create a basic scatterplot of the OLS residuals vs fitted values but select "With Groups" to mark the points by Discount.
  • Select Stat > Basic Statistics > Display Descriptive Statistics to calculate the residual variance for Discount=0 and Discount=1.
  • Select Calc > Calculator to calculate the weights variable = 1/variance for Discount=0 and Discount=1, Perform a linear regression analysis to fit a WLS model (click "Options" to set the weights variable and click "Storage" to store standardized residuals and fitted values).
  • Create a basic scatterplot of the WLS standardized residuals vs fitted values.

Home price (nonconstant variance and weighted least squares)