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Modern Regression Techniques Using R

Statistics is the language of modern empirical social and behavioural science and the varieties of regression form the basis of this;

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Advanced R Statistical Programming and Data Models

, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes;

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Regression Analysis with R

want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an;

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Regression Modeling Strategies

when developing multi-variable models using real data and not standard textbook examples. Regression Modelling Strategies presents full;

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Regression Modeling Strategies

when developing multi-variable models using real data and not standard textbook examples. Regression Modelling Strategies presents full;

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Introduction to Robust Estimation and Hypothesis Testing

nonparametric techniques. The practical importance of these varied methods is illustrated using data from real world studies. Over 1700 R functions are;

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A Modern Approach to Regression with R

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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R Statistics Cookbook

Perform t-tests, chi-squared tests, and regression analysis using modern statistical techniques Book DescriptionR is a popular programming;

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Applied Regression Analysis and Other Multivariable Methods

techniques, and valid interpretations of those techniques. Available with InfoTrac (R) Student Collections http://gocengage.com/infotrac.;

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Robust Nonlinear Regression

The first book to discuss robust aspects of nonlinear regression-with applications using R software Robust Nonlinear Regression: with;

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R In Finance And Economics

. It is specifically targeted towards undergraduate and graduate students. It provides beginner-level introduction to R using RStudio and;

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Categorical Data Analysis and Multilevel Modeling Using R

Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal;

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Linear Regression Analysis

computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the;

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Introduction to Robust Estimation and Hypothesis Testing

software. Modern robust methods provide improved techniques for dealing with outliers, skewed distribution curvature and heteroscedasticity that;

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Extending The Linear Model With R

Nonparametric Regression Models, Second Edition takes advantage of the greater functionality now available in R and substantially revises and adds;

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Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set

This set contains: 9780471469438 Regression and ANOVA: An Integrated Approach Using SAS(R) Software by Keith E. Muller, Bethel A. Fetterman;

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Extending the Linear Model with R

. Faraway's critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods;

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Semiparametric Regression

ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular;

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Semiparametric Regression

ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular;

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Method and Substance in Macrocomparative Analysis

, comparative employment performance in affluent countries, using three of the most common macrocomparative techniques: pooled cross-section time-series;

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Using R for Introductory Econometrics

modern resource. I know I'm going to be using it with my students, and I recommend it to anyone who wants to learn about econometrics and R at;

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Classroom Supplement to Regression Analysis and its Application

underlying the techniques utilized in regression analysis and illustrates their application on a variety of data sets.;

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Econometric Evaluation of Socio Economic Programs

of the treatment effects. By using both real and simulated data, readers will become familiar with evaluation techniques, such as regression;

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Dynamic Regression Models for Survival Data

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and;

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Statistical Regression and Classification

This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned;

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Dynamic Regression Models for Survival Data

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and;

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Graphics for Statistics and Data Analysis with R

these principles to engaging examples using the graphics and lattice packages in R. It offers a wide array of modern graphical displays for data;

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