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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 book covers the main models within the GLM (i.e., logistic, Poisson, negative binomial, ordinal, and multinomial). It focuses on graphic... Læs mere
R for Quantitative Chemistry is an exploration of how the R language can be applied to a wide variety of problems in what is typically termed "Quantitative Chemistry" or sometimes "Analytical Chemistry". This book will be based upon, in large part, actual experimental data.
R for Quantitative Chemistry is an exploration of how the R language can be applied to a wide variety of problems in what is typically termed "Quantitative Chemistry" or sometimes "Analytical Chemistry". This book will be based upon, in large part, actual experimental data.
There has been considerable attention to making the methodologies of structural equation modeling available to... Læs mere
Explores emerging and advanced techniques in food processing, such as ultrasound, microwave... Læs mere
Covering basic univariate and bivariate statistics and regression models for nominal, ordinal, and interval outcomes, this textbook provides... Læs mere
This book introduces the reader to data science using R and the tidyverse. No prerequisite knowledge is needed in college-level programming or mathematics (e.g., calculus or statistics). The book is self-contained so readers can immediately begin building data science workflows.
Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems.
The book is intended to serve as an introductory course in group theory geared towards second-year university students. The second part is the core of the book... Læs mere