## Classroom Supplement to Regression Analysis and its Application: A Data-Oriented Approach |

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### Contents

Section 1 | 1 |

Section 2 | 4 |

Section 3 | 7 |

Section 4 | 10 |

Section 5 | 13 |

Section 6 | 16 |

Section 7 | 20 |

Section 8 | 23 |

Section 9 | 26 |

Section 10 | 29 |

Section 11 | 32 |

Section 12 | 34 |

Section 13 | 47 |

### Common terms and phrases

acceptable fit ANOVA table assumed model backward elimination beta weights Calculate California SMSAs chapter Ck statistics Ck values coefficient of determination confidence intervals Cook's distance data base Data Set A.8 estimated coefficients F statistics forward selection given in eqn HC and NOX HOME identified indicator variable INDUS and METAL interval estimates land use variables least squares estimates Mortality and Pollution mortality rates observations original 15 predictor outliers pairwise correlations partial residual plots plot of WASTE Pollution Study prediction equation prediction interval previous exercise principal component regions regression analysis residual statistics response variable RETAIL and MISC ridge estimates ridge trace roots and latent scatterplots Section selection and backward Set B.2 single-variable regression model smallest latent roots Solid Waste Analysis solid waste produced SQRTME standardized coefficient standardized estimates strong multicollinearities studentized residuals subsets suggest Theoretical tion TOTAL variable selection variables in Data variance inflation factors vectors of W'W waste production