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R Language Tutorial for Mainframe Programmers

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IT+Jobs with R Language Skills
Why R? It's free, open source, powerful and highly extensible. "You have a lot of prepackaged stuff that's already available, so you're standing on the shoulders of giants," Google's chief economist told The New York Times back in 2009.

Learn to use R: Your hands-on guide

Part 1: Introduction
Part 2: Getting your data into R
Part 3: Easy ways to do basic data analysis
Part 4: Painless data visualization
Part 5: Syntax quirks you'll want to know
Part 6: Useful resources

Because it's a programmable environment that uses command-line scripting, you can store a series of complex data-analysis steps in R. That lets you re-use your analysis work on similar data more easily than if you were using a point-and-click interface, notes Hadley Wickham, author of several popular R packages and chief scientist with RStudio.

That also makes it easier for others to validate research results and check your work for errors -- an issue that cropped up in the news recently after an Excel coding error was among several flaws found in an influential economics analysis report known as Reinhart/Rogoff.

Why not R? Well, R can appear daunting at first. That's often because R syntax is different from that of many other languages, not necessarily because it's any more difficult than others.

How R is different from Excel?

The error itself wasn't a surprise, blogs Christopher Gandrud, who earned a doctorate in quantitative research methodology from the London School of Economics. "Despite our best efforts we always will" make errors, he notes. "The problem is that we often use tools and practices that make it difficult to find and correct our mistakes."

Sure, you can easily examine complex formulas on a spreadsheet. But it's not nearly as easy to run multiple data sets through spreadsheet formulas to check results as it is to put several data sets through a script, he explains.

Where to download R-Free version?

Click here -You can download here.

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