7.7 Prediction: Linear model (Equation) (1)

  • Linear Model = LM = Linear regression model
  • Aim (normally): Model (also understand) relationship between outcome variable (output) und 1+ explanatory variables (features)
\(y_{i} = \underbrace{\color{blue}{\beta_{0}} + \color{orange}{\beta _{1}} \times x_{1i} + \color{orange}{\beta _{2}} \times x_{2i}}_{?} + \underbrace{\color{red}{\varepsilon}_{i}}_{?}\)


  • Q: How do we also call \(\color{blue}{\beta_{0}}\), \(\color{orange}{\beta _{1}}\) and \(\color{orange}{\beta _{2}}\)?