Use R

Political Analysis Using R can serve as a textbook for undergraduate or graduate students as well as a manual for independent researchers. It is unique among competitor books in its usage of 21 example datasets that are all drawn from political research.

This book introduces the main theoretical findings related to copulas and shows how statistical modeling of multivariate continuous distributions using copulas can be carried out in the R statistical environment with the package copula (among others).

Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies. In the interest of reaching the widest possible audience of quality-control professionals and statisticians, examples throughout are structured to simplify complex equations and data structures, and to demonstrate their applications to quality control processes, such as ISO standards.

Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps. The philosophy behind the book is to start with real world raw datasets and perform all the analytical steps needed to reach final results. Though theory plays an important role, this is a practical book for advanced undergraduate and graduate classes in bioinformatics, genomics and statistical genetics or for use in lab sessions.

The first seven chapters use R for probability simulation and computation, including random number generation, numerical and Monte Carlo integration, and finding limiting distributions of Markov Chains with both discrete and continuous states. Applications include coverage probabilities of binomial confidence intervals, estimation of disease prevalence from screening tests, parallel redundancy for improved reliability of systems, and various kinds of genetic modeling.

Complete Data Science Bootcamp with 5 Capstone Projects: Mathematics, Statistics, R, Machine Learning

R, Python data science with R programming, handle with data, manipulate data and outcomes with R (programming language)