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R is a free and widely used program for statistical analysis that allows users to analyze data, create publication quality graphs, and utilize pre-existing packages to analyze different types of data through an importable coding language; while it has a learning curve, R has a large community of support and resources and is able to handle large data sets for most purposes; the document provides information on downloading and using basic functions in R as well as helpful links and tutorials for learning R.
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A brief introduction to 'R' statistical package
This document provides an introduction to R, an open-source statistical software environment. It discusses key features of R including its data handling, statistical, and graphical capabilities. The document also summarizes popular statistical methods that can be performed in R like correlation, regression, time series analysis, and discusses the advantages and disadvantages of using R.
1.3 introduction to R language, importing dataset in r, data exploration in r
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www.simpleresearch.net
info@simpleresearch.net
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A brief introduction to 'R' statistical package
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R program
- 1. The Project
- 2. What is R? A FREE program widely used for statistical analysis.
- 3. Why use R? Strengths - Free - Creates graphs that are publication-quality - Lots of code and packages have been written for it. You’re able to use packages that analyze biodiversity, the human genome, or speech patterns for example. - A wealth of support and resources
- 4. What is R? Limitations - Takes a bit of time to learn but may be well worth your while in the long run - Unable to handle very very verylarge quantities of data. For most purposes, R is great
- 5. This is your data
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- 9. Columns To recall the value of your columns OR
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Editor's Notes
- Here’s an introduction. I’ll give you the tools to learn, use and play with R, but I’m not an expert so I’m unlikely to answer your questions. I am, however, able to direct you to resources online.
- In order to use R, we must learn the language of R. It’s similar to MatLab and Stata. More sophisticated programs can be very costly (hundreds, upwards to thousands of dollars), but they’re designed to handle a TON of information. I’m not fluent in R, but I do know a few phrases and will walk through an example with you.
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- To use R, you must communicate with the program in it’s own language. Like learning all languages, the best way to get familiar with it is to use it in practice. So the first step is to download the program.
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