Hands-On Programming with R

Hands-On Programming with R

Author: Garrett Grolemund

Publisher: "O'Reilly Media, Inc."

ISBN: 9781449359119

Category: Computers

Page: 249

View: 796

Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools. RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time. Work hands-on with three practical data analysis projects based on casino games Store, retrieve, and change data values in your computer’s memory Write programs and simulations that outperform those written by typical R users Use R programming tools such as if else statements, for loops, and S3 classes Learn how to write lightning-fast vectorized R code Take advantage of R’s package system and debugging tools Practice and apply R programming concepts as you learn them

Doing Meta-Analysis with R

Doing Meta-Analysis with R

Author: Mathias Harrer

Publisher: CRC Press

ISBN: 9781000435634

Category: Mathematics

Page: 500

View: 942

Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book

R Programming for Beginners

R Programming for Beginners

Author: Nathan Metzler

Publisher:

ISBN: 171037411X

Category:

Page: 166

View: 304

Master the programming skills you need to turn raw, unfiltered data into deep insights and get ready for a data science and analytics career with this definitive guide to R Programming for Beginners! Do you want to get started learning how to program, but don't know where to begin? Are you interested in moving beyond Excel sheets and learning one of the most powerful programming language used in cutting edge research such as machine learning? If you answered yes to any of these questions, then this book might just be what you need. R can be a royal pain in the neck sometimes. Even seasoned programmers and data analysts still struggle with it. But it doesn't have to be you. In this guide, you're going to learn everything you need to do heavy data wrangling in R, with graded exercises and examples at the end to help you reinforce what you've learned. Here's a preview of what you're going to discover in R Programming for Beginners Step-by-step instructions to help you set up and install the R Environment with photos How to properly Execute R Scripts with your favorite code editor Everything you need to know about the R syntax-statements, blocks, comments, and keywords Steps to help you write your very first R script and begin your programming journey The 6 data types supported by the R programming language How to name variables and assign values to them Steps to help you write well-defined user functions effectively How to control program flow with decision making control structures and loops How to visualize data with R programming ...and lots more! Whether you're completely new to programming and have never written a single line of code before, or you're an intermediate or experienced R programmer looking to brush up on the basics, this book has everything you need to master R completely. Scroll to the top of the page and click the "Add to Cart" button to get started today!

Finite Element Computations in Mechanics with R

Finite Element Computations in Mechanics with R

Author: Khameel Bayo Mustapha

Publisher: CRC Press

ISBN: 9781351385596

Category: Science

Page: 368

View: 289

Finite Element Computations in Mechanics with R: A Problem-Centred Programming Approach provides introductory coverage of the finite element method (FEM) with the R programming language, emphasizing links between theory and implementation of FEM for problems in engineering mechanics. Useful for students, practicing engineers, and researchers, the text presents the R programming as a convenient easy-to-learn tool for analyzing models of mechanical systems, with finite element routines for structural, thermal, and dynamic analyses of mechanical systems, and also visualization of the results. Full-color graphics are used throughout the text.

Data Science with R for Psychologists and Healthcare Professionals

Data Science with R for Psychologists and Healthcare Professionals

Author: Christian Ryan

Publisher: CRC Press

ISBN: 9781000530568

Category: Business & Economics

Page: 312

View: 421

This introduction to R for students of psychology and health sciences aims to fast-track the reader through some of the most difficult aspects of learning to do data analysis and statistics. It demonstrates the benefits for reproducibility and reliability of using a programming language over commercial software packages such as SPSS. The early chapters build at a gentle pace, to give the reader confidence in moving from a point-and-click software environment, to the more robust and reliable world of statistical coding. This is a thoroughly modern and up-to-date approach using RStudio and the tidyverse. A range of R packages relevant to psychological research are discussed in detail. A great deal of research in the health sciences concerns questionnaire data, which may require recoding, aggregation and transformation before quantitative techniques and statistical analysis can be applied. R offers many useful and transparent functions to process data and check psychometric properties. These are illustrated in detail, along with a wide range of tools R affords for data visualisation. Many introductory statistics books for the health sciences rely on toy examples - in contrast, this book benefits from utilising open datasets from published psychological studies, to both motivate and demonstrate the transition from data manipulation and analysis to published report. R Markdown is becoming the preferred method for communicating in the open science community. This book also covers the detail of how to integrate the use of R Markdown documents into the research workflow and how to use these in preparing manuscripts for publication, adhering to the latest APA style guidelines.

Predictive Soil Mapping with R

Predictive Soil Mapping with R

Author: Tomislav Hengl

Publisher: Lulu.com

ISBN: 9780359306350

Category:

Page: 372

View: 664

Predictive Soil Mapping (PSM) is based on applying statistical and/or machine learning techniques to fit models for the purpose of producing spatial and/or spatiotemporal predictions of soil variables i.e. maps of soil properties and classes at different resolutions. It is a multidisciplinary field combining statistics, data science, soil science, physical geography, remote sensing, geoinformation science and a number of other sciences. Predictive Soil Mapping with R is about understanding the main concepts behind soil mapping, mastering R packages that can be used to produce high quality soil maps, and about optimizing all processes involved so that also the production costs can be reduced. The online version of the book is available at: https: //envirometrix.github.io/PredictiveSoilMapping/ Pull requests and general comments are welcome. These materials are based on technical tutorials initially developed by the ISRIC's Global Soil Information Facilities (GSIF) development team over the period 2014?2017

Efficient R Programming

Efficient R Programming

Author: Colin Gillespie

Publisher: "O'Reilly Media, Inc."

ISBN: 9781491950753

Category: Computers

Page: 220

View: 348

There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming. Get advice for setting up an R programming environment Explore general programming concepts and R coding techniques Understand the ingredients of an efficient R workflow Learn how to efficiently read and write data in R Dive into data carpentry—the vital skill for cleaning raw data Optimize your code with profiling, standard tricks, and other methods Determine your hardware capabilities for handling R computation Maximize the benefits of collaborative R programming Accelerate your transition from R hacker to R programmer

Building a Platform for Data-Driven Pandemic Prediction

Building a Platform for Data-Driven Pandemic Prediction

Author: Dani Gamerman

Publisher: CRC Press

ISBN: 9781000457193

Category: Medical

Page: 382

View: 651

This book is about building platforms for pandemic prediction. It provides an overview of probabilistic prediction for pandemic modeling based on a data-driven approach. It also provides guidance on building platforms with currently available technology using tools such as R, Shiny, and interactive plotting programs. The focus is on the integration of statistics and computing tools rather than on an in-depth analysis of all possibilities on each side. Readers can follow different reading paths through the book, depending on their needs. The book is meant as a basis for further investigation of statistical modelling, implementation tools, monitoring aspects, and software functionalities. Features: A general but parsimonious class of models to perform statistical prediction for epidemics, using a Bayesian approach Implementation of automated routines to obtain daily prediction results How to interactively visualize the model results Strategies for monitoring the performance of the predictions and identifying potential issues in the results Discusses the many decisions required to develop and publish online platforms Supplemented by an R package and its specific functionalities to model epidemic outbreaks The book is geared towards practitioners with an interest in the development and presentation of results in an online platform of statistical analysis of epidemiological data. The primary audience includes applied statisticians, biostatisticians, computer scientists, epidemiologists, and professionals interested in learning more about epidemic modelling in general, including the COVID-19 pandemic, and platform building. The authors are professors at the Statistics Department at Universidade Federal de Minas Gerais. Their research records exhibit contributions applied to a number of areas of Science, including Epidemiology. Their research activities include books published with Chapman and Hall/CRC and papers in high quality journals. They have also been involved with academic management of graduate programs in Statistics and one of them is currently the President of the Brazilian Statistical Association.

Measuring Productivity in Education and Not-for-Profits

Measuring Productivity in Education and Not-for-Profits

Author: Kenneth Moore

Publisher: Springer Nature

ISBN: 9783030729653

Category: Business & Economics

Page: 148

View: 570

This book takes the reader through real-world examples for how to characterize and measure the productivity and performance of NFPs and education institutions—that is, organisations that produce value for society, which cannot be measured accurately in financial KPIs. It focuses on how best to frame non-profit performance and productivity, and provides a suite of tools for measurement and benchmarking. It further challenges the reader to consider alternative and appropriate uses of quantitative measures, which are fit-for-purpose in individual contexts. It is true that the risk of misusing quantitative measures is ever-present. But does that risk outweigh the benefits of forming a more precise and shared understanding of what could generate better outcomes? There will always be concerns about policy and performance management. Goodheart’s Law states that once a measure becomes a target, it is no longer a good measure. This book helps to strike a meaningful balance between what can be measured, what cannot, and how best to use quantitative information in sectors that are often averse to being held up to the light and put on a scale by outsiders.

Hands On PLC Programming with RSLogix 500 and LogixPro

Hands On PLC Programming with RSLogix 500 and LogixPro

Author: Eman Kamel

Publisher: McGraw Hill Professional

ISBN: 9781259644351

Category: Technology & Engineering

Page:

View: 589

Master the art of PLC programming and troubleshooting Program, debug, and maintain high-performance PLC-based control systems using the detailed information contained in this comprehensive guide. Written by a pair of process automation experts, Hands-On PLC Programming with RSLogixTM 500 and LogixPro® lays out cutting-edge programming methods with a strong focus on practical industrial applications. Homework questions and laboratory projects illustrate important points throughout. A start-to-finish capstone design project at the end of the book illustrates real-world uses for the concepts covered. Inside: • Introduction to PLC control systems and automation • Fundamentals of PLC logic programming • Timer and counter programming • Math, move, comparison, and program control instructions • HMI design and hardware configuration • Process control design and troubleshooting • Instrumentation and process control • Analog programming and advanced control • Comprehensive case studies