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Introduction to Linear Regression Analysis, 6th Edition

INTRODUCTION TO LINEAR REGRESSION ANALYSIS A comprehensive and current introduction to the fundamentals of regression analysis;

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Linear Regression Analysis

This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical;

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Regression Analysis and Linear Models

, generalized linear model, etc. This book presents the complex subject of regression analysis and linear models, in the most comprehensible and easy to;

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Simultaneous Inference in Regression

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods;

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Simultaneous Inference in Regression

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods;

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Applied Regression Analysis and Generalized Linear Models

Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the;

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Applied Linear Regression 4th Ed

modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world;

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Sensitivity Analysis in Linear Regression

This volume treats linear regression diagnostics as a tool for the application of linear regression models to real-life data. The;

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Applied Regression Analysis

This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data;

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Applied Regression Analysis

This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data;

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Partially Linear Models

In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing;

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Methods And Applications Of Linear Models

thoroughly updated book, Methods and Applications of Linear Models: Regression and the Analysis of Variance, Third Edition features innovative;

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Linear Regression

This text introduces the fundamental linear regression models used in quantitative research. It covers both the theory and application;

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Modeling in Mathematics

and its application to energy-growth consumption problem. This book also discusses about intuitionistic fuzzy weighted linear regression model;

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Focus on Nonlinear Analysis Research

from oxygen saturation recordings using non-linear regression analysis; non-linearity in bridge structural analysis; non-linear analysis;

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Advanced Linear Models

prediction. The authors discuss the application of statistical theories and methodologies to various linear models such as the linear regression;

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Statistical Methods for the Analysis of Biomedical Data

The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear;

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An Introduction to Generalized Linear Models

this foundation, the authors explore multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival;

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An Introduction to Generalized Linear Models

this foundation, the authors explore multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival;

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An Introduction to Generalized Linear Models

multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival analysis, multilevel modeling, Bayesian;

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Linear Regression: A Mathematical Introduction

Taking the reader step-by-step through the intricacies, theory and practice of regression analysis, Damodar N. Gujarati uses a clear style;

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Applied Regression Analysis and Experimental Design

For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis;

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Applied Regression Analysis and Experimental Design

For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis;

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Introductory Statistics with R

introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.;

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Extending The Linear Model With R

count models, linear discriminant analysis, and sandwich and robust estimation for generalized linear models (GLMs) Revised chapters on random;

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