R for Everyone: Advanced Analytics and Graphics 1st Edition, authored by Jared P. Lander is a book that helps students understand and use the R language. The author helps us understand R by drawing on his extensive experience in teaching students through the New York City R User Group. 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 The 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 you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll 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, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this, you'll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most.
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About the Author
Jared P. Lander is the Chief Data Scientist of Lander Analytics, a New York-based data science firm that specializes in statistical consulting and training services, the organizer of the New York Open Statistical Programming "Meetup"—the world’s largest R meetup—and the New York R Conference and an adjunct professor of statistics at Columbia University. His writings on statistics can be found and been featured in publications such as Forbes and the Wall Street Journal.