| Description |
ix, 216 pages : illustrations ; 24 cm |
| Bibliography |
Includes bibliographical references (pages 210-212) and index. |
| Contents |
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. |
| Subject |
Regression analysis.
|
|
Regression analysis. |
| ISBN |
0306456486 |
|
