Learn R
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Learn R
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Author : Pedro J. Aphalo
language : en
Publisher: CRC Press
Release Date : 2020-07-28
Learn R written by Pedro J. Aphalo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-28 with Computers categories.
Learning a computer language like R can be either frustrating, fun, or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward on overcoming them. This book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. Although rarely mentioned separately, fluency in a computer programming language involves both writing and reading. The parallels between natural and computer languages are many, but differences are also important. For students and professionals in the biological sciences, humanities, and many applied fields, recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide, encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2020 and beyond. Features R as it is currently used Few prescriptive rules—mostly the author’s preferences together with alternatives Explanation of the R grammar emphasizing the "R way of doing things" Tutoring for "programming in the small" using scripts The grammar of graphics and the grammar of data described as grammars Examples of data exchange between R and the foreign world using common file formats Coaching for becoming an independent R user, capable of both writing original code and solving future challenges What makes this book different from others: Tries to break the ice and help readers from all disciplines feel at home with R Does not make assumptions about what the reader will use R for Attempts to do only one thing well: guide readers into becoming fluent in the R language Pedro J. Aphalo is a PhD graduate from the University of Edinburgh, and is currently a lecturer at the University of Helsinki. A plant biologist and agriculture scientist with a passion for data, electronics, computers, and photography, in addition to plants, Dr. Aphalo has been a user of R for 25 years. He first organized an R course for MSc students 18 years ago, and is the author of 13 R packages currently in CRAN.
Learn R Programming In 24 Hours
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Author : Alex Nordeen
language : en
Publisher: Guru99
Release Date : 2020-10-31
Learn R Programming In 24 Hours written by Alex Nordeen and has been published by Guru99 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-31 with Computers categories.
R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?
R Programming For Beginners
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Author : Nathan Metzler
language : en
Publisher:
Release Date : 2019-11-22
R Programming For Beginners written by Nathan Metzler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-22 with categories.
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!
R Programming For Beginners
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Author : Peter Simon
language : en
Publisher: Peter Simon
Release Date :
R Programming For Beginners written by Peter Simon and has been published by Peter Simon this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
R Programming for Beginners: Master the Fundamentals of R, Even with Zero Coding Experience The Ultimate Beginner’s Guide to Learning R—Perfect for First-Time Coders, Data Enthusiasts, and Future Analysts! Ready to dive into the world of data but not sure where to start? Whether you're exploring data science with R, planning to take an R programming online course, or just curious about coding, R Programming for Beginners is your go-to guide for mastering the essentials of the R programming language—no technical background needed. This book is more than just a read—it's a hands-on R course for beginners that walks you step by step through real-world examples, making learning R programming for beginners simple, effective, and even fun. 🔍 What This R Programming Book Covers: ✅ Introduction to R Software for Beginners Learn what R is, how to install and use R Studio for beginners, and why it's one of the top tools for data analysis and statistical computing. ✅ Essential R Programming Language Basics Master the core concepts: Data types and variables Vectors, matrices, and data frames Control structures (if statements, loops) Writing custom functions Basic R programs for data manipulation and cleaning ✅ Hands-On Practice for Real Learning Apply what you learn with practical examples and exercises—just like a real R programming course for beginners or an R programming tutorial for beginners would provide. 🎯 Why This Is the Best Way to Learn R Programming Online: 📘 Structured Like an R Programming Language Online Course – With clear progression and learning checkpoints. 💡 Beginner-Friendly Explanations – No jargon. Just step-by-step help for anyone who wants to learn R programming the right way. 💻 Perfect Alternative to an R Software Online Course – Learn at your own pace, with full control. 📊 Built for Data Analysis – This is not just theory—you'll learn how to apply R to real data. 🔧 Your First Step into Data Science with R – Ideal for building a strong foundation before advancing to machine learning, statistics, or big data. 👨🏫 Who This R Programming Training Is For: Absolute beginners who want a friendly R language tutorial for beginners Students looking to learn R language for beginners without overwhelming content Professionals starting a data career and seeking an easy-to-follow R software tutorial for beginners Self-learners who want a book-based R programming language course that replaces expensive bootcamps Anyone interested in R programming for dummies-style guidance, minus the fluff 🎁 Bonus Learning Tools Included: Practice datasets and sample code Clear R exercises with solutions Downloadable materials via our R language website Recommendations for the best tools to learn R language online Guidance on how to continue with an R programming online course after completing this book ✅ Start Your R Coding Journey Today If you’ve been searching for a beginner R tutorial that makes sense, or a way to learn R programming without frustration, this is the book for you. Whether you’re taking your first steps or using it as a supplement to an R programming language online course, this beginner guide will help you learn R language fast and with confidence. 🛒 Scroll up and get your copy today—start your journey with R, the powerful programming language for data science, now!
R
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Author : Acodemy
language : en
Publisher:
Release Date : 2015-03-15
R written by Acodemy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-15 with categories.
R Programming LanguageAre You Ready to Know All About R Programming? Learning a programming language is not an easy work. It requires time, money and desire. You must search an academy or a teacher, achieve coordination with them, or worse, adapt your own time to their class times. You also have to pay the high fees, month to month, and what is even more annoying is this: you will probably have to go to a special place in order to practice the new programming language! I made this crash course for a reason... I made this course to give YOU a solution. This crash course about R programming is not only going to teach you the basics of R in a didactic way, furthermore, you will learn R language WHEN you want, and more important, WHERE you want (It could even be at your home!). I made this crash course to show you HOW you can learn R programming FASTER than you ever thought possible. I will teach YOU step by step the R Language extremely quickly. I will TAKE you through a step by step guide where you simply can't get lost! This course-book will allow you to practice, learn and deepen your knowledge of R as a new programming language in an entertaining, interactive, autonomous and flexible course. Stop procrastinating and start NOW! Learning the R Language is something that is a really worth investing time. R programming Language course is now available in Amazon and it is just for $10,99. This is a no-brainer!Crash it!Here Is A Preview Of What You'll Learn When You Download You Copy Today: What is R Programming? What is R used for? Getting Started with R programming Writing Code and Text Editors Reading Files with Functions in R programming Symbols and Assignments Conditional and Repetitive Executions Loops and Vectorization Apply Loop Family Sequences Data Manipulation Vectors Text Processing Text Manipulation Working With Data Frames Matrix and Arrays Generic Functions and S3 Classes Writing R Packages Much, much more! Download your copy today!To order your copy, click the BUY button and download it right now!(c) 2014 All Rights ReservedR Programming: Learn R Programming FAST - The Ultimate Crash Course to Learning the Basics of R Programming Language In No TimeRemember: Investing in yourself is the most important thing to do!
Learn R Programming In 1 Day
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Author : Krishna Rungta
language : en
Publisher:
Release Date : 2019-09-10
Learn R Programming In 1 Day written by Krishna Rungta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-10 with categories.
R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, d104 File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?
Learn R For Applied Statistics
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Author : Eric Goh Ming Hui
language : en
Publisher: Apress
Release Date : 2018-11-30
Learn R For Applied Statistics written by Eric Goh Ming Hui and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Computers categories.
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R’s syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions. Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations. What You Will Learn Discover R, statistics, data science, data mining, and big data Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions Work with descriptive statistics Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions Who This Book Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.
The Variorum Teacher S Edition Of The Holy Bible
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Author : William Sanday
language : en
Publisher:
Release Date : 1886
The Variorum Teacher S Edition Of The Holy Bible written by William Sanday and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1886 with categories.
M Z
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Author : Alexander Schmidt
language : en
Publisher:
Release Date : 1886
M Z written by Alexander Schmidt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1886 with categories.
R Programming
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Author : Daniel Daniel Bell
language : en
Publisher:
Release Date : 2020-06
R Programming written by Daniel Daniel Bell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06 with categories.
2020- Second Edition, updated version. Get your copy!! Why Learn R? What are the reasons to learn R for Data Science? In this small textbook recommended for absolute beginners, the author tried to answer these types of questions. After reading this guide, maybe in one or two days, you will learn the basics of R programming and its utility for each Data Scientist. Indeed, R is a programming language and software environment for statistical analysis, graphics representation, and reporting. If you are trying to understand the R programming language as a beginner, this short book will give you enough understanding of almost all the concepts of the R language. The author will guide you through examples, how to program in R and how to use R for effective data analysis.Get your copy Now! Book Objectives This book is about R programming. The following are the objectives of the author: To familiarize you with the basics of R programming language. To help you understand the various fields where R can be applied and its use cases in each field. To equip you with R programming skills, both beginner and advanced skills. To introduce you to R programming for data analysis. To introduce you to R programming for machine learning. To help you understand and appreciate the power of R in statistical computing, data analysis, and scientific research. Who this Book is for? Anybody who is a complete beginner to R Programming. Anybody in need of advancing their R Programming skills. Professionals in computer programming. Professors, lecturers or tutors who are looking to find better ways to explain R programming to their students in the simplest and easiest way. Students and academicians, especially those focusing on R, Data Analysis,Machine Learning , computer science, and Databases development. Requirements The author expects you to have a computer installed with an operating system such as Linux, Windows or Mac OS X. What is inside the book? R BASICS R DATA TYPES R VARIABLES AND CONSTANTS R OPERATORS DECISION MAKING IN R R LOOPS R FUNCTIONS R CLASSES AND OBJECTS R FOR DATA SCIENCE R FOR MACHINE LEARNING From the Back Cover. R programming language is one of the most popular languages used by statisticians, data analysts, researchers to retrieve, clean, analyze, visualize and present data. This is a comprehensive book on how to get started with R programming, why you should learn it and how you can learn it. Daniel Bell begins by introducing the readers to the foundations of the R programming language. The aim is to help you understand, how the R interpreter works, the origin of the name R, how to set up the R programming environment, etc. The author has discussed the process of installing R on Windows, Linux and Mac OS. Moreover, the author has explored the basics of R programming including writing comments, using the R console, creating R script files, etc. The various features provided by R have been discussed in depth, including data types, variables, loops, decision making, functions, operators, classes, and objects, etc. The author has also discussed R for data science and R for machine learning. The book has been organized into chapters, with each chapter having many sub-chapters. R code scripts have been provided, alongside thorough explanations of the code and images showing the expected output upon the execution of every script. Get your copy