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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

Statistics in R

First steps

| Lund University
| University of Paris VIII

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.

Keywords: cross-tabulation, dataframe, formatting data, importing data
Published online: 6 November 2014
DOI logo
https://doi.org/10.1075/hcp.43.13wei
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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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