Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models.
Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models.
Exploring Linear Algebra: Labs and Projects with MATLAB(R) is a hands-on lab manual that can be used by students and instructors in classrooms every day to guide the exploration of the theory and applications of linear algebra.
Thoroughly updated throughout, A First Course in Linear Model Theory, Second Edition is an intermediate-level statistics text that fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students.
Multiple Imputation in Practice: With Examples Using IVEware provides practical guidance on multiple imputation analysis, from simple to complex problems using real and simulated data sets.
Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of variables.
Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times.
For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems.
For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems.
Written for those with little or no experience in using computers for statistical analysis, this book introduces SPSS/PC+, the market leader PC package.
This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results.
This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results.
The new edition of An Introduction to Statistical Concepts is designed to help students really understand statistical concepts, the situations in which they can be used, and how to apply them to data.
The new edition of An Introduction to Statistical Concepts is designed to help students really understand statistical concepts, the situations in which they can be used, and how to apply them to data.
This book is designed to explain the fundamental principles of automatic control through 20 lessons, each incorporating worked examples and MATLAB(R)-based exercises to help readers effectively understand and apply the proposed methods.
Marketing researchers, companies and business schools need to be able to use statistical procedures correctly and accurately interpret the outputs, yet generally these people are scared off by the statistics behind the different analyses procedures, thus they often rely on external sources to come up with profound answers to the proposed research questions.
Marketing researchers, companies and business schools need to be able to use statistical procedures correctly and accurately interpret the outputs, yet generally these people are scared off by the statistics behind the different analyses procedures, thus they often rely on external sources to come up with profound answers to the proposed research questions.
Choose the Proper Statistical Method for Your Sensory Data Issue Analyzing Sensory Data with R gives you the foundation to analyze and interpret sensory data.
The First Book to Explain How a User of R or MATLAB Can Benefit from the OtherIn today's increasingly interdisciplinary world, R and MATLAB(R) users from different backgrounds must often work together and share code.
Learn How to Use Growth Curve Analysis with Your Time Course Data An increasingly prominent statistical tool in the behavioral sciences, multilevel regression offers a statistical framework for analyzing longitudinal or time course data.
Choose the Proper Statistical Method for Your Sensory Data Issue Analyzing Sensory Data with R gives you the foundation to analyze and interpret sensory data.
The First Book to Explain How a User of R or MATLAB Can Benefit from the OtherIn today's increasingly interdisciplinary world, R and MATLAB(R) users from different backgrounds must often work together and share code.
Learn How to Use Growth Curve Analysis with Your Time Course Data An increasingly prominent statistical tool in the behavioral sciences, multilevel regression offers a statistical framework for analyzing longitudinal or time course data.
Since the publication of this book's bestselling predecessor, Mathematica(R) has matured considerably and the computing power of desktop computers has increased greatly.
Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data.
