Primer of applied regression & analysis of variance
Author(s)
Bibliographic Information
Primer of applied regression & analysis of variance
McGraw-Hill, Medical Pub. Division, c2001
2nd ed
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
Applicable for all statistics courses or practical use, this book teaches how to understand more advanced multivariate statistical methods as well as how to use available software packages to get correct results. With clear and entertaining writing style, it demystifies a very dry, difficult subject. Study problems at the end of each chapter and examples culled from biomedical research illustrate key points.
Table of Contents
Why Do Multivariate Analysis?. The First Step: Understanding Simple Linear Regression. Regression With Two or More Independent Variables. Do the Data Fit the Assumptions?. Multicollinearity and What to Do About It. Selecting the "Best" Regression Model. One-Way Analysis of Variance. Two-Way Analysis of Variance. Repeated Measures. Mixing Continuous and Categorical Variables: Analysis of Covariance. Nonlinear Regression. Regression With a Qualitative Dependent Variable. APPENDIX A. A Brief Introduction to Matrices and Vectors. APPENDIX B. Statistical Package Cookbook. APPENDIX C. Data for Examples. APPENDIX D. Data for Problems. APPENDIX E. Statistical Tables. APPENDIX F. Solutions to Problems.
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