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Basic Statistics provides an accessible and comprehensive introduction to statistics using the free, state-of-the-art software program R. This book is designed to... Læs mere
This book unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks and decision trees under a common umbrella; namely, the conditional distribution model.
This book covers medium to advanced content about Shiny, so it will help people that are already familiar with building apps with Shiny, and who want to go one step further.
Mathematical modeling is both a skill and an art and must be practiced in order to maintain and enhance the ability to use those skills. This book will be of interest to instructors and students offering courses focused on discrete modeling or modeling for decision making.
Statistical Trend Analysis of Physically Unclonable Functions first presents a review on cryptographic hardware and hardware-assisted cryptography. Afterwards, the authors present a combined survey and research work on PUFs using a systematic approach.
This textbook is designed for an undergraduate course in data science that emphasizes topics in both statistics and computer science.
Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies.
This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation.
This innovative textbook and online resource package equips students with the tools needed to develop a working knowledge of finite... Læs mere
In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize... Læs mere
Introduces new graph theory techniques for the analysis and integration of multi-type large data sets) in the life sciences. Discussing... Læs mere