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...

Buy Now From Amazon

Product Review

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.



Similar Products

The Seven Pillars of Statistical WisdomBayes Theorem Examples: An Intuitive GuideMake Your Own Neural NetworkMastering 'Metrics: The Path from Cause to Effect