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This book is an integrated treatment of applied statistical methods, presented at an intermediate level. It serves as an advanced introduction to the SAS programming language as well as demonstrating how to use SAS to analyse of a wide variety of data.
In particular, it focuses on a truncated exponential family of distributions with a natural parameter and truncation parameter as a typical... Læs mere
The book provides relationships of the autoregressive linear mixed effects models with linear mixed effects models, marginal models, transition models, nonlinear mixed effects models, growth curves, differential equations, and state space representation.
This text, which uses MATLAB, gives a detailed overview of structured programming and numerical methods for the undergraduate student.The... Læs mere
Applied Business Statistics for Business and Management using Microsoft Excel is the first book to illustrate the capabilities of Microsoft Excel to teach applied statistics effectively.
This book presents recent non-asymptotic results for approximations in multivariate statistical analysis. It then introduces new... Læs mere
This book is the modern first treatment of experimental designs, providing a comprehensive introduction to the interrelationship between the theory of optimal designs and the theory of cubature formulas in numerical analysis.
Providing a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences.
Geared toward social and behavioural statistics students, especially those with no background in computer science, this handy guide contains basic information on statistics in the R language.
An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis.