7.11 Prediction: Linear model (Prediction)

yLeia=5.56+0.66×x1Leia+0.12×x2Leia+εLeia

5=5.56+0.66×0+0.12×1+0.69=5.69+0.69

Name trust2006 \boldsymbol{\color{blue}{\beta_{0}}} \boldsymbol{\color{orange}{\beta_{1}}} victim2006 \boldsymbol{\color{orange}{\beta_{2}}} education2006 \boldsymbol{\color{red}{\varepsilon}} \color{green}{\widehat{y}}
Daniel 5 5.56 -0.66 1 0.12 1 -0.02 5.02
Leia 5 5.56 -0.66 0 0.12 1 -0.69 5.69
Harrison 7 5.56 -0.66 0 0.12 5 0.81 6.19
.. .. .. .. .. .. .. .. ..
  • Important note on “prediction”
    • We can predict outcome values of units that are part of the sample on which the model is based
    • Objective of machine learning (ML) is to predict outcome values of units that were NOT part of the sample on which the model is based (trained)