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R^{2} is also known as the coefficient of determination.

Term | Description |
---|---|

y _{i} | i ^{th} observed response value |

mean response | |

i ^{th} fitted response |

While the calculations for adjusted R^{2} can produce negative values, Minitab displays zero for these cases.

Term | Description |
---|---|

i^{th} observed response value | |

i^{th} fitted response | |

mean response | |

n | number of observations |

p | number of terms in the model |

While the calculations for R^{2}(pred) can produce negative values, Minitab displays zero for these cases.

Term | Description |
---|---|

y _{i} | i ^{th} observed response value |

mean response | |

n | number of observations |

e _{i} | i ^{th} residual |

h _{i} | i ^{th} diagonal element of X(X'X)^{–1}X' |

X | design matrix |

Term | Description |
---|---|

SSE_{p} | sum of squared errors for the model under consideration |

MSE_{m} | mean square error for the model with all predictors |

n | number of observations |

p | number of terms in the model, including the constant |

Term | Description |
---|---|

MSE | mean square error |