Through the use of careful explanation and examples, Berry demonstrates how to consider whether the assumptions of multiple regression are actually satisfied in a particular research project. Beginning with a brief review of the regression assumptions as they are typically presented in text books, he moves on to explore in detail the substantive meaning of each assumption; for example, lack of measurement error, absence of specification error, linearity, homoscedasticity, and lack of auto-correlation.Through the use of careful explanation and examples, Berry demonstrates how to consider whether the assumptions of multiple regression are actually satisfied in a particular research project.

Title | : | Understanding Regression Assumptions |

Author | : | William D. Berry |

Publisher | : | SAGE - 1993-02-25 |

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