Difference between revisions of "R for Large Scale Data Analysis"
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This tutorial focuses on using R for large amounts of data. It deals with three different topics: managing data, analysing data, as well as basic and intermediate plotting. Each topic is accompanied by a short introduction, overview of experiences, as well as recommended packages. The tutorial itself is hands-on. We will look at different possibilities and solutions. |
This tutorial focuses on using R for large amounts of data. It deals with three different topics: managing data, analysing data, as well as basic and intermediate plotting. Each topic is accompanied by a short introduction, overview of experiences, as well as recommended packages. The tutorial itself is hands-on. We will look at different possibilities and solutions. |
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The tutorial targets participants who already have some basic experiences with programming but do not necessarily know much about R. |
The tutorial targets participants who already have some basic experiences with programming but do not necessarily know much about R. |
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| + | The workshop material can be found at [[Media:Handout.zip]]. |
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Revision as of 00:54, 9 September 2015
The R programming language is a free software environment for statistical computing and graphics. It is widely used among statisticians and data miners. But especially the huge variety of available packages will make the introduction into daily business far from easy. This tutorial focuses on using R for large amounts of data. It deals with three different topics: managing data, analysing data, as well as basic and intermediate plotting. Each topic is accompanied by a short introduction, overview of experiences, as well as recommended packages. The tutorial itself is hands-on. We will look at different possibilities and solutions. The tutorial targets participants who already have some basic experiences with programming but do not necessarily know much about R.
The workshop material can be found at Media:Handout.zip.
