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An exploration of regression graphics through computer graphics. Recent developments in computer technology have stimulated new and;
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This book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme;
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of analyses. Topics discussed include assessing association in contingency tables and sets of tables, logistic regression and conditional logistic;
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Updates to this new edition include: more coverage of regression assumptions and model fit; additional material on residual analysis; more;
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of regression analysis. Both research statisticians and users of statistics should find this book generally both interesting and accessible. `A;
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It is no exaggeration to say that virtually all quantitative research in the social sciences is done with correlation and regression;
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Master the fundamentals of regression without learning calculus with this one-stop resource The newly and thoroughly revised 3rd;
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Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression;
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, including pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for;
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Over the years, I have had the opportunity to teach several regression courses, and I cannot think of a better undergraduate text than this;
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Analysis of Failure and Survival Data is an essential textbook for graduate-level students of survival analysis and reliability and a;
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Analysis of Failure and Survival Data is an essential textbook for graduate-level students of survival analysis and reliability and a;
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Nonparametric Regression Models, Second Edition takes advantage of the greater functionality now available in R and substantially revises and adds;
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inference, linear correlation and regression, dummy variables and interaction effects, and logistic regression. The clear explanation and;
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Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques;
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Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques;
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Regression - this book covers all regression techniques and their implementation in R A complete guide to building effective regression models in R;
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polynomial modeling in the standard, logistic, and Poisson regression contexts with continuous, discrete, and counts outcomes, respectively, either;
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including descriptive statistics, correlation and simple regression, t tests, one-way chi square, data transformations, multiple regression;
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including descriptive statistics, correlation and simple regression, t tests, one-way chi square, data transformations, multiple regression;
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This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear;
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This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear;
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Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods;
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Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods;
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Perform t-tests, chi-squared tests, and regression analysis using modern statistical techniques Book DescriptionR is a popular programming;
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Handbook of Regression Methods concisely covers numerous traditional, contemporary, and nonstandard regression methods. The handbook;
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