R Basics with Tabular Data
As more and more historical records are digitized, having a way to quickly analyze large volumes of tabular data makes research faster and more effective. R is a programming language with strengths in statistical analyses. As such, it can be used to complete quantitative analysis on historical so...
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| Format: | Article |
| Language: | English |
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Editorial Board of the Programming Historian
2016-12-01
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| Series: | The Programming Historian |
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| Online Access: | http://programminghistorian.org/lessons/r-basics-with-tabular-data |
| Summary: | As more and more historical records are digitized, having a way to quickly analyze large volumes of tabular data makes research faster and more effective.
R is a programming language with strengths in statistical analyses. As such, it can be used to complete quantitative analysis on historical sources, including but not limited to statistical tests. Because you can repeatedly re-run the same code on the same sources, R lets you analyze data quickly and produces repeatable results. Because you can save your code, R lets you re-purpose or revise functions for future projects, making it a flexible part of your toolkit.
This tutorial presumes no prior knowledge of R. It will go through some of the basic functions of R and serves as an introduction to the language. It will take you through the installation process, explain some of the tools that you can use in R, as well as explain how to work with data sets while doing research. The tutorial will do so by going through a series of mini-lessons that will show the kinds of sources R works well with and examples of how to do calculations to find information that could be relevant to historical research. The lesson will also cover different input methods for R such as matrices and using CSV files. |
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| ISSN: | 2397-2068 2397-2068 |