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Blog archive ### Getting into R: R Tutorials

As Big Data and data analytics become more critical business functions, developers are turning more to R to support data mining and analysis apps. And since it's open source, you can incorporate R apps into your arsenal of business apps and keep the data divers happy. Whether you're new to R or looking to ramp up your R game, here are a few R tutorial blogs that can keep you on the right track.

#### Cyclismo.Org

This free R tutorial was created by Kelly Black, who is a grad student in mathematics at the University of Georgia. Who better to help you get into R? This is a good introductory level tutorial if you're just getting started, or have a bit of experience with R but need to sharpen up your skills. As indicated on the post, more than 100,000 people have already worked their way through this tutorial.

1. Input
2. Basic Data Types
3. Basic Operations and Numerical Descriptions
4. Basic Probability Distributions
5. Basic Plots
6. Intermediate Plotting
7. Indexing into Vectors
8. Linear Least Squares Regression
9. Calculating Confidence Intervals
10. Calculating p Values
11. Calculating The Power of a Test
12. Two Way Tables
13. Data Management
14. Time Data Types
15. Introduction to Programming
16. Object Oriented Programming
17. Case Study: Working Through a HW Problem
18. Case Study II: A JAMA Paper on Cholesterol

I found the case studies particularly interesting. The JAMA case study examines a paper that appeared in the Journal of the American Medical Association, and use R to confirm the results of cholesterol testing and results. That's definitely putting R to some good use. If you like what you see here, the author of this post Kelly Black has also written a book about programming R called: R Object Oriented Programming, published by Packt Publishing.

#### R Tutorial

Well, you certainly couldn't ask for a more straightforward name. This handy tutorial even helps you download R to get started. Download R from one of the Comprehensive R Archives Network sites at: http://cran.r-project.org/mirrors.html. This tutorial, the post says, is background material for their primary tutorial series Elementary Statistics with R.

Having found that elementary statistics with R tutorial, I dug deeper into that. This tutorial take you through the following statistical topics, and shows how you can address the problems with R:

• Qualitative Data
• Quantitative Data
• Numerical Measures
• Probability Distributions
• Interval Estimation
• Hypothesis Testing
• Type II Error
• Goodness of Fit
• Analysis of Variance
• Non-parametric Methods
• Simple Linear Regression
• Multiple Linear Regression
• Logistic Regression

The post describes the tutorial elements as follows: "The R solutions are short, self-contained and requires minimal R skill. Most of them are just a few lines in length. With simple modifications, the code samples can be turned into homework answers. In additional to helping with your homework, the tutorials will give you a taste of working with statistics software in general, and it will prove invaluable in the success of your career." This ought to set you well on your way to smoother number crunching with R.

Posted by Lafe Low on 10/27/2017 at 11:39 AM