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This article discusses how applied statistics can enhance data analysis in second language acquisition (SLA) research. It advocates for the use of visual summaries like boxplots over barplots and introduces robust statistical methods that are less sensitive to normality assumptions, such as trimmed means and bootstrapping. The authors emphasize the importance of these techniques for improving the reliability and accuracy of statistical analyses in SLA studies.

Author

Geovanny Pena Perez

Language

EN