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In:Corpus Methods for Semantics: Quantitative studies in polysemy and synonymy
Edited by Dylan Glynn and Justyna A. Robinson
[Human Cognitive Processing 43] 2014
► pp. 343–364

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Statistics in R

First steps

 | Lund University
 | University of Paris VIII
Published online: 6 November 2014
DOI logo with link
https://doi.org/10.1075/hcp.43.13wei
The R Project for Statistical Computing is one of the most comprehensive and widely used software options for statistical analysis. Moreover, it is open source, freely available and entirely cross-platform. It is for these reasons that the following chapters all employ R to demonstrate the application and interpretation of statistics. Like the commercially available software SAS, but unlike three other widely used suites (SPSS, Stata, and Statistica), R is principally used in command line. The need to work with commands rather than a graphical user interface can be a challenge for novice users, especially when combined with the task of learning statistics. However, commands given in a step-by-step fashion is arguably simpler than a graphic interface, which can overwhelm the novice user with options. This chapter is an introduction to R focusing on how to import data and make sure those data are in the correct format for analysis. Knowledge of each of these steps is assumed in the following chapters.
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Cited by (1)

Cited by one other publication

González Granado, Nicolás, Patrick Drouin & Aurélie Picton
2023. De l’analyse statistique à l’apprentissage automatique : le langage R au service de la terminologie. Éla. Études de linguistique appliquée N° 208:4 ► pp. 447 ff. DOI logo

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