Details

R All-in-One For Dummies


R All-in-One For Dummies


1. Aufl.

von: Joseph Schmuller

25,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 04.01.2023
ISBN/EAN: 9781119983705
Sprache: englisch
Anzahl Seiten: 688

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Beschreibungen

<p><b>A deep dive into the programming language of choice for statistics and data</b></p> <p>With <i>R All-in-One For Dummies</i>, you get five mini-books in one, offering a complete and thorough resource on the R programming language and a road map for making sense of the sea of data we're all swimming in. Maybe you're pursuing a career in data science, maybe you're looking to infuse a little statistics know-how into your existing career, or maybe you're just R-curious. This book has your back. Along with providing an overview of coding in R and how to work with the language, this book delves into the types of projects and applications R programmers tend to tackle the most. You'll find coverage of statistical analysis, machine learning, and data management with R.</p> <ul> <li>Grasp the basics of the R programming language and write your first lines of code</li> <li>Understand how R programmers use code to analyze data and perform statistical analysis</li> <li>Use R to create data visualizations and machine learning programs </li> <li>Work through sample projects to hone your R coding skill</li> </ul> <p>This is an excellent all-in-one resource for beginning coders who'd like to move into the data space by knowing more about R.</p>
<p>Introduction 1</p> <p><b>Book 1: Introducing R 5</b></p> <p>Chapter 1: R: What It Does and How It Does It 7</p> <p>Chapter 2: Working with Packages, Importing, and Exporting 37</p> <p><b>Book 2: Describing Data 51</b></p> <p>Chapter 1: Getting Graphic 53</p> <p>Chapter 2: Finding Your Center 93</p> <p>Chapter 3: Deviating from the Average 103</p> <p>Chapter 4: Meeting Standards and Standings 113</p> <p>Chapter 5: Summarizing It All 125</p> <p>Chapter 6: What’s Normal? 145</p> <p><b>Book 3: Analyzing Data 163</b></p> <p>Chapter 1: The Confidence Game: Estimation 165</p> <p>Chapter 2: One-Sample Hypothesis Testing 181</p> <p>Chapter 3: Two-Sample Hypothesis Testing 207</p> <p>Chapter 4: Testing More than Two Samples 233</p> <p>Chapter 5: More Complicated Testing 257</p> <p>Chapter 6: Regression: Linear, Multiple, and the General Linear Model 279</p> <p>Chapter 7: Correlation: The Rise and Fall of Relationships 315</p> <p>Chapter 8: Curvilinear Regression: When Relationships Get Complicated 335</p> <p>Chapter 9: In Due Time 359</p> <p>Chapter 10: Non-Parametric Statistics 371</p> <p>Chapter 11: Introducing Probability 393</p> <p>Chapter 12: Probability Meets Regression: Logistic Regression 415</p> <p><b>Book 4: Learning from Data 423</b></p> <p>Chapter 1: Tools and Data for Machine Learning Projects 425</p> <p>Chapter 2: Decisions, Decisions, Decisions 449</p> <p>Chapter 3: Into the Forest, Randomly 467</p> <p>Chapter 4: Support Your Local Vector 483</p> <p>Chapter 5: K-Means Clustering 503</p> <p>Chapter 6: Neural Networks 519</p> <p>Chapter 7: Exploring Marketing 537</p> <p>Chapter 8: From the City That Never Sleeps 557</p> <p><b>Book 5: Harnessing R: Some Projects to Keep You Busy 573</b></p> <p>Chapter 1: Working with a Browser 575</p> <p>Chapter 2: Dashboards — How Dashing! 603</p> <p>Index 639</p>
<p><b>Joseph Schmuller</b> is a cognitive scientist and statistical analyst. His recent work in the <i>For Dummies</i> series includes the 5th edition of <i>Statistical Analysis with Excel For Dummies</i> along with <i>Statistical Analysis with R For Dummies</i> and <i>R Projects For Dummies.</i>
<p><b>Crunch any number of numbers with R</b> <p>When there’s data about, R is the coding language of choice. This book helps you take charge of your data with the R programming language so you can build datasets, automate data analysis and machine learning tasks, and create visual outputs to communicate your findings. Even if you’re new to programming, these simple instructions will get you started handling tasks usually reserved for data scientists. Find distributions and averages, test statistical hypotheses, create decision trees and neural networks, and put the answers you find into helpful dashboards and visualizations. And do it all the easy way, with this easy-to-understand guide. <p><b>5 Mini-Books Inside…</b> <ul><li>Introducing R</li> <li>Describing Data</li> <li>Analyzing Data</li> <li>Learning From Data</li> <li>Harnessing R: Some Projects to Keep You Busy</li></ul>

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