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02 September 2022
Today we have another huge addition of books to the library, now consisting at 350 R programming books! Thanks to Gary and Abraham for the additions!
Using Spark from R for performance with arbitrary code
by Jozef Hajnala
This book provides practical insights into using the sparklyr interface to gain the benefits of Apache Spark while still retaining the ability to use R code organized in custom-built functions and packages.
https://www.bigbookofr.com/big-data.html#using-spark-from-r-for-performance-with-arbitrary-code
Big Data with R – Exercise book
by James Blair
This 2-day workshop covers how to analyze large amounts of data in R. We will focus on scaling up our analyses using the same dplyr verbs that we use in our everyday work. We will use dplyr with data.table, databases, and Spark. We will also cover best practices on visualizing, modeling, and sharing against these data sources. Where applicable, we will review recommended connection settings, security best practices, and deployment options.
https://www.bigbookofr.com/big-data.html#big-data-with-r—exercise-book
Fundamentals of Wrangling Healthcare Data with R
by J. Kyle Armstrong
“In this course we will review some of the tools of the trade, namely, R’s tidyverse (Wickham and Grolemund 2017; Winter 2019) – a collection of R packages designed with a common framework to aide in common data wrangling and data management tasks.
Data Wrangling is one subset set of skills within the Data Science Process. We will carefully investigate how decisions made while collecting and preparing the data have down-stream effects on model performance.”
Data Science for Economists and Other Animals
by Grant McDermott
Introduce Economics graduate students to the modern data science toolkit
https://www.bigbookofr.com/finance.html#data-science-for-economists-and-other-animals
Applied longitudinal data analysis in brms and the tidyverse
by A Solomon Kurz
A translation of the examples and figures from Singer and Willett’s classic Applied longitudinal data analysis: Modeling change and event occurrence.
Recoding Introduction to Mediation, Moderation, and Conditional Process Analysis
by A Solomon Kurz
A translation of the code from the second edition of Andrew F. Hayes’s Introduction to Mediation, Moderation, and Conditional Process Analysis.
An R Exercise in Data Collection, Cleaning, and Merging U.S. Census Data
by Sean Conner
A step-by-step walkthrough exercise using U.S. Census data.
Bayesian Hierarchical Models in Ecology
by Steve Midway
Hierarchical Models in Ecology Using Bayesian Inference
https://www.bigbookofr.com/life-sciences.html#bayesian-hierarchical-models-in-ecology
Advanced Regression Methods – Companion to BER642
by Cheng HUA
Different multiple regression methods are presented including an overview of ordinary least squares regression, ordinal regression, logistic and probit regression, loglinear, mixed, and regression discontinuity. Interpretation of results diagnostics, and appications are covered for the several glm models.
https://www.bigbookofr.com/statistics.html#advanced-regression-methods—companion-to-ber642
Little Book of R for Biomedical Statistics
by Avril Coghlan
This is a simple introduction to biomedical statistics using the R statistics software.
https://www.bigbookofr.com/life-sciences.html#little-book-of-r-for-biomedical-statistics
A Little Book of R for Time Series
by Avril Coghlan
This is a simple introduction to time series analysis using the R statistics software.
https://www.bigbookofr.com/statistics.html#a-little-book-of-r-for-time-series
A Little Book of R for Multivariate Analysis
by Avril Coghlan
This is a simple introduction to multivariate analysis using the R statistics software.
https://www.bigbookofr.com/statistics.html#a-little-book-of-r-for-multivariate-analysis
A Little Book of R for Bioinformatics
by Avril Coghlan
This is a simple introduction to bioinformatics, with a focus on genome analysis, using the R statistics software.
https://www.bigbookofr.com/life-sciences.html#a-little-book-of-r-for-bioinformatics
Circular Visualization in R
by Zuguang GU
This is the documentation of the circlize R package.
https://www.bigbookofr.com/packages.html#circular-visualization-in-r
The R Manuals
by R Development Core team
This is a restyled version of the R manuals, originally provided by the R Development Core team.
https://www.bigbookofr.com/r-programming.html#the-r-manuals
Reproducible Analytical Pipelines (RAP) Companion
by Matthew Gregory
Reproducible Analytical Pipelines require a range of tools and techniques to implement that can be a challenge to overcome, and this book address some of the common knowledge gaps and hard-to-Google problems that upcoming RAP-pers face.
The Turing Way
by The Turing Way Community
The Turing Way is a handbook to reproducible, ethical and collaborative data science. We involve and support a diverse community of contributors to make data science accessible, comprehensible and effective for everyone. Our goal is to provide all the information that researchers and data scientists in academia, industry and the public sector need at the start of their projects to ensure that they are easy to reproduce at the end.
https://www.bigbookofr.com/career-and-community.html#the-turing-way
Applied Microeconometrics with R
by Achim Zeileis
“This project will gradually turn the course materials for the “Econometrics and Statistics: Microeconometrics” course at Universität Innsbruck into an online book.
The topics covered roughly follow the book Analysis of Microdata by Winkelmann & Boes (2009, Springer-Verlag) and encompass: models for categorical responses (binary, multinomial, ordered), count data, limited dependent variables, and duration models.”
https://www.bigbookofr.com/finance.html#applied-microeconometrics-with-r
Flexible Regression Models
by Nikolaus Umlauf
This script aims to cover the core knowledge of flexible regression models, frequentist and Bayesian estimation, computational details and software implementations. The script assumes a certain basic knowledge of the linear regression model and the generalized linear model (GLM).
https://www.bigbookofr.com/statistics.html#flexible-regression-models
Data Analytics
by Achim Zeileis
This collection of R tutorials accompanies the new course Data Analytics organized jointly in the bachelor curriculum “Wirtschaftswissenschaften” and the complementary subject area “Digital Science” at Universität Innsbruck and its Digital Science Center (DiSC).
https://www.bigbookofr.com/statistics.html#data-analytics
Larger-Than-Memory Data Workflows with Apache Arrow
by Danielle Navarro
In this tutorial you will learn how to use the arrow R package to create seamless engineering-to-analysis data pipelines. You’ll learn how to use interoperable data file formats like Parquet or Feather for efficient storage and data access. You’ll learn how to exercise fine control over data types to avoid common data pipeline problems. During the tutorial you’ll be processing larger-than-memory files and multi-file datasets with familiar dplyr syntax, and working with data in cloud storage.
https://www.bigbookofr.com/big-data.html#larger-than-memory-data-workflows-with-apache-arrow
Web Scraping with R
by Steve Pittard
Web Scraping with R. A rich source of examples and instruction.
https://www.bigbookofr.com/getting-cleaning-and-wrangling-data.html#web-scraping-with-r
Analysing Data using Linear Models
by Stéphanie M. van den Berg
“This book is for bachelor students in social, behavioural and management sciences that want to learn how to analyse their data, with the specific aim to answer research questions. The book has a practical take on data analysis: how to do it, how to interpret the results, and how to report the results. All techniques are presented within the framework of linear models: this includes simple and multiple regression models, linear mixed models and generalised linear models. This approach is illustrated using R.”
https://www.bigbookofr.com/statistics.html#analysing-data-using-linear-models
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The post 23 New books added to Big Book of R appeared first on Oscar Baruffa.
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