In the first book that directly uses R to teach data analysis, Linear Models with R focuses on the practice of regression and analysis of variance. It clearly demonstrates the different methods available and more importantly, in which situations each one applies. It covers all of the standard topics, from the basics of estimation to missing data, factorial designs, and block designs, but it also includes discussion on topics, such as model uncertainty, rarely addressed in books of this type. The presentation incorporates an abundance of examples that clarify both the use of each technique and the conclusions one can draw from the results. All of the data sets used in the book are available for download from the Internet.Includes bibliograph...
This highly anticipated second edition features new chapters and sections, 225 new references, and c...
This easy-to-follow applied book expands upon the authors’ prior work on semiparametric regression t...
Methods of Statistical Model Estimation examines the most important and popular methods used to esti...
This textbook presents an introduction to multiple linear regression, providing real-world data sets...
Includes full text in PDF, supplemental data in .csv, and supplemental data in .RLinear Regression U...
This book presents key modeling and prediction techniques, along with relevant applications. Topics ...
Linear Models, and Related Methods, is an introduction to linear models that begins with least squar...
Key words:regression analysis model;statistics with R; linear Abstract:Multiple regression analysis ...
The 2nd edition of R for Marketing Research and Analytics continues to be the best place to learn R ...
This book demonstrates the importance of computer-generated statistical analyses in behavioral scien...
Regression is the branch of Statistics in which a dependent variable of interest is modelled as a li...
This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path m...
Integrates the theory and applications of statistics using R A Course in Statistics with R has been ...
There are many books that are excellent sources of knowledge about individual statistical tools (sur...
This easy-to-follow applied book expands upon the authors’ prior work on semiparametric regression t...
This highly anticipated second edition features new chapters and sections, 225 new references, and c...
This easy-to-follow applied book expands upon the authors’ prior work on semiparametric regression t...
Methods of Statistical Model Estimation examines the most important and popular methods used to esti...
This textbook presents an introduction to multiple linear regression, providing real-world data sets...
Includes full text in PDF, supplemental data in .csv, and supplemental data in .RLinear Regression U...
This book presents key modeling and prediction techniques, along with relevant applications. Topics ...
Linear Models, and Related Methods, is an introduction to linear models that begins with least squar...
Key words:regression analysis model;statistics with R; linear Abstract:Multiple regression analysis ...
The 2nd edition of R for Marketing Research and Analytics continues to be the best place to learn R ...
This book demonstrates the importance of computer-generated statistical analyses in behavioral scien...
Regression is the branch of Statistics in which a dependent variable of interest is modelled as a li...
This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path m...
Integrates the theory and applications of statistics using R A Course in Statistics with R has been ...
There are many books that are excellent sources of knowledge about individual statistical tools (sur...
This easy-to-follow applied book expands upon the authors’ prior work on semiparametric regression t...
This highly anticipated second edition features new chapters and sections, 225 new references, and c...
This easy-to-follow applied book expands upon the authors’ prior work on semiparametric regression t...
Methods of Statistical Model Estimation examines the most important and popular methods used to esti...