2 Motivation

Documenting techniques for teaching pronunciation or related speech communication aspects and comparing the effects of such techniques are important aspects to advance our current understanding of beneficial strategies in phonetics education. These processes, however, may be sometimes challenging because of unfamiliarity with the appropriate tools for performing related tasks such as statistical analysis, plotting results, etc.

Relative interest over time for different statistics programming language across the world. A value of 100 indicates a peak of popularity of the term as measured by Google Trends.

Figure 2.1: Relative interest over time for different statistics programming language across the world. A value of 100 indicates a peak of popularity of the term as measured by Google Trends.

R, a rich environment for statistical analysis, can be considered as one of those underused tools in the field since despite of its benefits some consider it a language with a rather flat learning curve: compared with other languages, the time required to perform a similar task is greater in R.

Luckily, there’s a vibrant community of users and developers that are generous with explanations and forgiving with novices, which eases this learning process for the interested ones. In the last decade there has been a growing interest on R worldwide while interest in other traditional software for statistics declines, as shown in Figure 2.1 (Google Trends).

The objective of this workshop is to address common hurdles that researchers in phonetics may face in the process of data analysis using R. Little or no knowledge of R is expected from the audience. At the end of this workshop, attendees should be able to perform Repeated Measures Analysis of Variance—RM-ANOVA in R, as well as producing figures, tables, etc. relevant to their work.