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By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely used statistical technique is accessible to readers who may have only a rudimentary knowledge of mathematics. Chapters discuss: -descriptive statistics using vector notation and the components of a simple regression model; -the logic of sampling distributions and simple hypothesis testing; -the basic operations of matrix algebra and the properties of the multiple regression model; -testing compound hypotheses and the application of the regression model to the analyses of variance and covariance, and -structural equation models and influence statistics.
By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely
′The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articl
Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose
Intuitively understand regression analysis by focusing on concepts and graphs rather than equations and formulas. I use everyday language so you can grasp regre
Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using con
