Understanding regression analysis /

• Κύριος συγγραφέας: Allen, Michael Patrick
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York : Plenum Press, �1997.
• Θέματα: Regression analysis.; Statistics.; Matrices.; Structural equation modeling.; MATHEMATICS > Probability & Statistics > Regression Analysis.; Electronic books.

 Proceeding on the assumption that it is possible to develop a sufficient understanding of this technique without resorting to mathematical proofs and statistical theory, Understanding Regression Analysis explores 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; the testing of compound hypotheses and the application of the regression model to the analysis of variance and covariance; and structural equation models and influence statistics. 

 Origins and uses of regression analysis --   Basic matrix algebra: manipulating vectors --   Mean and variance of a variable --   Regression models and linear functions --   Errors of prediction and least-squares estimation --   Covariance and linear independence --   Separating explained and error variance --   Transforming variables to standard form --   Regression analysis with standardized variables --   Populations, samples, and sampling distributions --   Sampling distributions and test statistics --   Testing hypotheses using the t test --   t test for the simple regression coefficient --   More matrix algebra: manipulating matrices --   Multiple regression model --   Normal equations and partial regression coefficients --   Partial regression and residualized variables --   Coefficient of determination in multiple regression --   Standard errors of partial regression coefficents --   Incremental contributions of variables --   Testing simple hypotheses using the f test --   Testing for interaction in multiple regression --   Nonlinear relationships and variable transformations --   Regression analysis with dummy variables --   One-way analysis of variance using the regression model --   Two-way analysis of variance using the regression model --   Testing for interaction in analysis of variance --   Analysis of covariance using the regression model --   Interpreting interaction in analysis of covariance --   Structural equation models and path analysis --   Computing direct and total effects of variables --   Model specification in regression analysis --   Influential cases in regression analysis --   Problem of multicollinearity --   Assumptions of ordinary least-squares estimation --   Beyond ordinary regression analysis.