Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. Youâll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what youâve learned along the way.
Youâll learn how to:
Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals
Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution.
Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality youâll need to accomplish 80 percent of modern data tasks.
Landerâs self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. Youâll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, youâll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this youâll make your code reproducible with LaTeX, RMarkdown, and Shiny.
By the time youâre done, you wonât just know how to write R programs, youâll be ready to tackle the statistical problems you care about most.
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Gain better insight into your data using the power of R
While R is very flexible and powerful, it is unlike most of the computer programs you have used. In order to unlock its full potential, this book delves into the language, making it accessible so you can tackle even the most complex of data analysis tasks. Simple data examples are integrated throughout so you can explore the capabilities and versatility of R. Along the way, you'll also learn how to carry out a range of commonly used statistical methods, including Analysis of Variance and Linear Regression. By the end, you'll be able to effectively and efficiently analyze your data and present the results.
Discusses how to implement some basic statistical methods such as the t-test, correlation, and tests of association
Explains how to turn your graphs from merely adequate to simply stunning
Provides you with the ability to define complex analytical situations
Demonstrates ways to make and rearrange your data for easier analysis
Covers how to carry out basic regression as well as complex model building and curvilinear regression
Shows how to produce customized functions and simple scripts that can automate your workflow
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Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that guides you through all the techniques involved.
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Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2 Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more.
R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2 Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide.
R For Dummies, 2 Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.
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