Statistical Analysis with R For Dummies
- 5h 13m
- Joseph Schmuller
- John Wiley & Sons (US)
- 2017
Understanding the world of R programming and analysis has never been easier
Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming.
People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results.
- Gets you up to speed on the #1 analytics/data science software tool
- Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling
- Shows you how R offers intel from leading researchers in data science, free of charge
- Provides information on using R Studio to work with R
Get ready to use R to crunch and analyze your data—the fast and easy way!
About the Author
Joseph Schmuller, PhD, has taught undergraduate and graduate statistics, and has 25 years of IT experience. The author of four editions of Statistical Analysis with Excel For Dummies and three editions of Teach Yourself UML in 24 Hours (SAMS), he has created online coursework for Lynda.com and is a former Editor in Chief of PC AI magazine. He is a Research Scholar at the University of North Florida.
In this Book
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Introduction
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Data, Statistics, and Decisions
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R—What it Does and How it Does it
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Getting Graphic
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Finding Your Center
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Deviating from the Average
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Meeting Standards and Standings
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Summarizing it All
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What's Normal?
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The Confidence Game—Estimation
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One-Sample Hypothesis Testing
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Two-Sample Hypothesis Testing
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Testing More than Two Samples
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More Complicated Testing
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Regression—Linear, Multiple, and the General Linear Model
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Correlation—The Rise and Fall of Relationships
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Curvilinear Regression—When Relationships Get Complicated
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Introducing Probability
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Introducing Modeling
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Ten Tips for Excel Emigrés
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Ten Valuable Online R Resources
