# Statistical Computing

# UE STADA

## by Jaroslava Kankova

This is an online resource developed to support students attending the UE STADA class at the University of Vienna, Austria. You can use the chapter overview on the left to skip through the content. In this session, we will answer the following questions: R is a programming language used mostly for statistical computing and data visualization. Why are we using R and not other software such as SPSS? In this class we will be working in RStudio. The following picture illustrates the difference between R and RStudio: R as the Engine: RStudio as the dashboard: Just as a car needs both an engine and a … Read more →

# An Introduction to ggplot2

## by Ozancan Ozdemir

A ggplot2 Tutorial […] Hi! Data Visualization is one of the important steps of the data analysis process. It is actually not only part of the data analysis, but also can be considered as an art. R Programming language provides a powerful visualization package to us, ggplot2. This book aims to show how you can make a well-known statistical plots by using ggplot2, and also how you can improve or customize them. The book is created by the lab notes of statistical computing (STAT 291-STAT 292) of Ozancan Ozdemir. For your opinions and suggestions, please send me an e-mail to … Read more →

# Kinesiska

## by cda

Kinesiska […] R is a programming language and environment for statistical computing and graphics. This brief guide will get you … Read more →

# Advanced Statistical Computing

## by Roger D. Peng

The book covers material taught in the Johns Hopkins Biostatistics Advanced Statistical Computing course. I taught this course off and on from 2003–2016 to upper level PhD students in Biostatistics. The course ran for 8 weeks each year, which is a fairly compressed schedule for material of this nature. Because of the short time frame, I felt the need to present material in a manner that assumed that students would often be using others’ software to implement these algorithms but that they would need to know what was going on underneath. In particular, should something go wrong with one of … Read more →

# Efficient R programming

## by Colin Gillespie, Robin Lovelace

Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency. […] This is the online version of the O’Reilly book: Efficient R programming. Pull requests and general comments are welcome. Get a hard copy from: Amazon (UK), Amazon (USA), O’Reilly Colin Gillespie is Senior Lecturer (Associate Professor) at Newcastle University, UK. He is an Executive Editor of the R Journal, with research interests including high performance statistical computing and Bayesian statistics. Colin founded the … Read more →

# Population Health Data Science with R

## by Tomás J. Aragón

Population health data science (PHDS). […] We are writing this book to introduce R—a programming language and environment for statistical computing and graphics—to public health epidemiologists, health care data analysts, data scientists, statisticans, and others conducting population health analyses. Recent graduates come prepared with a solid foundation in epidemiological and statistical concepts and skills. However, what is sometimes lacking is the ability to implement new methods and approaches they did not learn in school. This is more apparent today with the emergence of data science … Read more →